Preparing for a Scala interview as a middle developer requires more than recalling syntax. Companies expect you to reason about type systems, concurrency, and functional design. Practicing targeted Scala interview questions for middle developers helps you surface weak spots, refine how you explain trade-offs, and demonstrate the depth that separates a mid-level candidate from the rest.
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Getting Ready for a Middle Scala Developer Interview
Middle-level interviews sit between foundational checks and deep architectural discussions. Recruiters need to confirm that candidates with three to five years of experience can operate independently, while developers need practice material that reflects real team expectations. Whether you are reviewing Scala interview questions for 3 years experience or refining answers closer to the Scala interview questions for 5 years experience range, the categories below cover the ground most interviewers walk.
How Scala Interview Questions Help Recruiters Assess Middles
A well-chosen middle Scala developer interview question reveals more than memorised definitions. It shows whether a candidate can reason about variance, evaluate concurrency trade-offs, and apply functional patterns in production code. Structured question sets reduce interviewer bias and produce comparable scorecards across rounds. McKinsey research shows that between 20 and 30 percent of critical roles are not filled by the most appropriate people, reinforcing why skills-focused evaluation matters. A shared bank of Scala interview questions for 4 years experience gives hiring panels a reliable baseline for every candidate.
How Sample Scala Interview Questions Help Middle Developers Improve Skills
For middle developers, working through realistic questions bridges the gap between daily coding and interview performance. Comparing bad and good answer pairs trains you to structure responses around reasoning rather than surface-level recall. The World Economic Forum reports that 44 percent of workers’ core skills will be disrupted by 2027, making continuous, deliberate practice essential for staying competitive. If you are moving up from entry level Scala interview questions, these middle-tier problems sharpen the depth interviewers expect. Once you are comfortable here, expert Scala interview questions become the natural next step.
List of 100 Scala Interview Questions for Middle Developers
The questions are organised into five sections by topic and difficulty. Each section starts with five detailed questions that include both a bad and a good answer so you can see common mistakes alongside strong responses. The remaining questions provide a correct answer only for faster review. Together they form a comprehensive set of middle level Scala interview questions that reflect what Scala developer interview questions for middle level roles typically cover.
Basic Middle Scala Developer Interview Questions
These Scala interview questions for middle-level developers cover the type system, language constructs, and core concepts that a developer with several years of experience should explain confidently.
1: What is variance in Scala and what are its forms?
Bad answer: Variance is about how variables change over time.
Good answer: Variance describes how subtyping of type parameters relates to subtyping of parameterised types. Covariant (+A) means List[Cat] is a subtype of List[Animal]. Contravariant (-A) reverses the relationship. Invariant types have no subtyping relationship at all.
2: What are upper and lower type bounds?
Bad answer: They limit how large or small a number can be.
Good answer: Upper bounds (A <: B) restrict a type parameter A to be a subtype of B. Lower bounds (A >: B) restrict A to be a supertype of B. They constrain generic parameters in classes and methods to ensure type safety.
3: What is the type class pattern in Scala?
Bad answer: A type class is a class that stores different types.
Good answer: A type class is a trait defining behaviour for a type without requiring that type to extend it. Instances are provided as implicit values (Scala 2) or given instances (Scala 3), enabling ad-hoc polymorphism and retroactive extension of third-party types.
4: How does implicit resolution work in Scala 2?
Bad answer: The compiler picks the first implicit it finds at random.
Good answer: The compiler searches the local scope first (imports, local definitions), then the implicit scope (companion objects of all involved types). If multiple candidates match, the most specific one wins. Otherwise the compiler reports an ambiguity error.
5: What are self types and how do they differ from inheritance?
Bad answer: Self types and inheritance are the same mechanism.
Good answer: A self type (self: OtherTrait =>) declares a dependency without creating an inheritance relationship. The class must mix in the required trait, but the self-typed trait does not inherit its methods. This gives more flexible composition than extends.
6: What is the difference between abstract types and type parameters?
Answer: Abstract types are declared inside a trait with type T and can be overridden in subclasses. Type parameters are declared on the trait itself. Abstract types allow path-dependent typing.
7: What is a context bound?
Answer: [A: Ordering] is shorthand for an implicit parameter of type Ordering[A]. It declares that a type class instance must exist for the type parameter.
8: What is a value class and what are its limitations?
Answer: A value class extends AnyVal and wraps a single field without allocating an object at runtime. Limitations include no lazy vals, no secondary constructors, and boxing when used as a trait instance.
9: What is a by-name parameter?
Answer: A by-name parameter (=> T) is evaluated each time it is referenced, not when the method is called. It enables lazy evaluation and is used in control abstractions.
10: What is the difference between def, val, and lazy val in a trait?
Answer: def is re-evaluated on every call. val is evaluated once during construction. lazy val is evaluated once on first access. Each has different initialisation timing.
11: What is a package object?
Answer: A package object holds methods, values, and type aliases accessible to all classes in the package. In Scala 3, top-level definitions replace package objects.
12: Why would you use multiple parameter lists?
Answer: Multiple parameter lists enable partial application, improve type inference, separate implicit parameters, and let the last list accept a block as a lambda.
13: How do given/using in Scala 3 differ from implicits in Scala 2?
Answer: given instances replace implicit val/def. using clauses replace implicit parameters. Scala 3 separates providing and requesting context values, making intent clearer.
14: What is an opaque type in Scala 3?
Answer: An opaque type creates a new type backed by an existing type without runtime overhead. Outside the defining scope the underlying type is hidden, providing type safety.
15: What is linearization in Scala?
Answer: Linearization determines the order in which traits are initialised and methods are resolved. Scala linearises right to left, removing duplicates while preserving order.
16: What is a path-dependent type?
Answer: A path-dependent type is tied to a specific instance. obj.Inner is a different type for each enclosing object, enabling type-safe relationships between instances.
17: What is structural typing?
Answer: Structural typing lets a type be defined by its methods and fields rather than its name. It uses reflection at runtime and is less performant than nominal typing.
18: What are existential types in Scala 2?
Answer: Existential types abstract over an unknown type parameter, written as List[_]. Scala 3 replaces them with wildcard arguments and match types.
19: What is the difference between a type alias and an opaque type?
Answer: A type alias is transparent and the compiler treats it as the underlying type everywhere. An opaque type hides the underlying type outside its definition scope.
20: What are extension methods in Scala 3?
Answer: Extension methods add new methods to existing types without modifying them. They replace the implicit class pattern from Scala 2.
21: How do Scala 3 enums differ from Scala 2 Enumeration?
Answer: Scala 3 enums are algebraic data types that support pattern matching, parameterised cases, and exhaustiveness checks. Scala 2 Enumeration is a simpler value-based approach.
22: What is an export clause in Scala 3?
Answer: Export clauses forward selected members of an object or class to the enclosing type, enabling composition-based delegation as an alternative to inheritance.
23: What is multiversal equality?
Answer: Multiversal equality restricts == comparisons to types that have a CanEqual instance, preventing comparison of unrelated types at compile time.
24: What is a dependent function type?
Answer: A dependent function type lets the return type depend on the argument value: (x: T) => x.Out. It enables richer type-level programming.
25: What is inline in Scala 3?
Answer: inline ensures a method or value is expanded at compile time. Combined with transparent inline it enables compile-time evaluation and type specialisation.
Middle Scala Developer Programming Interview Questions
These questions focus on functional programming patterns, concurrency, and effect systems that middle developers are expected to work with daily.
1: What is a Monad in Scala and which standard types are Monads?
Bad answer: A Monad is a design pattern for creating objects.
Good answer: A Monad is a type constructor with flatMap and pure (unit) that satisfies associativity and identity laws. Option, List, Future, Either, and IO are all Monads. They enable sequential composition of effectful computations.
2: How does Future handle concurrency in Scala?
Bad answer: Future runs code on a single thread like a queue.
Good answer: Future wraps a computation that runs asynchronously on a thread from the provided ExecutionContext. It is eagerly evaluated and its result is memoised. Results are accessed through callbacks (onComplete) or combinators (map, flatMap).
3: What is the difference between Future and IO in Cats Effect?
Bad answer: IO is just a newer version of Future with the same behaviour.
Good answer: Future is eagerly evaluated and not referentially transparent; creating a Future immediately starts execution. IO is a lazy description of an effect that only runs when explicitly executed, making it composable, testable, and safe for retries.
4: What is the difference between Try, Either, and Validated?
Bad answer: They all do the same thing but have different names.
Good answer: Try catches exceptions and wraps them as Failure. Either represents one of two outcomes and short-circuits in for-comprehensions. Validated (from Cats) accumulates all errors instead of short-circuiting, making it ideal for form or input validation.
5: What is referential transparency and why does it matter?
Bad answer: It means the code is transparent and easy to read.
Good answer: An expression is referentially transparent if it can be replaced by its value without changing program behaviour. It enables equational reasoning, safe refactoring, and predictable concurrency because expressions produce no side effects.
6: What does a for-comprehension desugar to?
Answer: Generators desugar to flatMap, the final generator to map, if guards to withFilter, and assignments to intermediate val bindings inside the chain.
7: What is the Cats library used for?
Answer: Cats provides type class abstractions (Functor, Monad, Applicative) and data types (Validated, NonEmptyList, EitherT) for functional programming in Scala.
8: What is ZIO and how does it differ from Cats Effect?
Answer: ZIO is an effect system built around ZIO[R, E, A] with built-in dependency injection (R) and typed errors (E). Cats Effect uses IO[A] with separate mechanisms for errors and dependencies.
9: What is a Promise in Scala?
Answer: A Promise is a writable, single-assignment container that produces a Future. You complete it with success or failure and the associated Future resolves with that result.
10: What is an ExecutionContext and how do you choose one?
Answer: ExecutionContext provides the thread pool for running Futures. Use the global pool for CPU-bound work and a fixed or cached pool for blocking IO.
11: What are parallel collections in Scala?
Answer: Parallel collections distribute operations across threads. They improve throughput for CPU-bound tasks but add overhead for small collections and are non-deterministic in order.
12: What is an Akka actor?
Answer: An actor is a lightweight concurrent entity that processes messages sequentially from a mailbox. Actors communicate through asynchronous message passing and encapsulate mutable state safely.
13: What is a supervision strategy in Akka?
Answer: A supervision strategy defines how a parent actor handles child failures: resume, restart, stop, or escalate. It enables self-healing through hierarchical fault tolerance.
14: What is Akka Streams?
Answer: Akka Streams processes data with backpressure using a Source-Flow-Sink model. It ensures producers do not overwhelm consumers.
15: What is the Writer Monad?
Answer: Writer[W, A] pairs a computation result with an accumulated log. W must be a Monoid, enabling logging without side effects.
16: What is the Reader Monad?
Answer: Reader[R, A] wraps a function R => A, representing a computation that depends on an environment. It is used for dependency injection without framework support.
17: What is the State Monad?
Answer: State[S, A] encapsulates S => (S, A), threading state through sequential computations without mutable variables.
18: What is a Monad Transformer?
Answer: A Monad Transformer stacks effects, for example EitherT[Future, Error, A] combines Future and Either in a single for-comprehension.
19: What is Kleisli?
Answer: Kleisli[F, A, B] wraps a function A => F[B] and enables composition of effectful functions. It is equivalent to Reader when F is Id.
20: What is Resource in Cats Effect?
Answer: Resource.make(acquire)(release) ensures a resource is released regardless of success or failure. It composes with flatMap for nested resource management.
21: What is IOApp in Cats Effect?
Answer: IOApp provides a main entry point for IO-based applications. It manages the runtime, handles interruption, and returns an ExitCode.
22: What is fibre-based concurrency?
Answer: Fibres are lightweight user-space threads managed by the effect runtime. They allow millions of concurrent tasks without OS thread overhead.
23: What is an effect system?
Answer: An effect system tracks computational effects (IO, errors, state) in the type signature, making side effects explicit. Cats Effect and ZIO are Scala effect systems.
24: What is trampolining?
Answer: Trampolining converts deep recursion into a heap-based loop by wrapping recursive calls in a data structure. It prevents stack overflow for non-tail-recursive algorithms.
25: How do you compose multiple independent effects?
Answer: Use Applicative combinators (mapN, tupled) or parMapN for independent effects. Unlike flatMap, Applicative does not impose sequencing, enabling parallelism.
Middle Scala Developer Coding Interview Questions
These questions test the ability to write, read, and reason about non-trivial Scala code. They go beyond entry level and reflect the kind of problems middle developers solve in production systems.
1: Implement a type class with a syntax extension method.
Bad answer: Create an abstract class and extend it for each type.
Good answer: Define trait Show[A] { def show(a: A): String }. Provide given instances for specific types. Add extension (a: A) def show(using s: Show[A]): String = s.show(a). Callers then write 42.show without importing implementation details.
2: Write a generic function that finds the maximum element using an implicit Ordering.
Bad answer: def max(list: List[Int]) = list.max. This only works for Int.
Good answer: def maxElem[A: Ordering](xs: List[A]): A = xs.reduce((a, b) => if (implicitly[Ordering[A]].gt(a, b)) a else b). The context bound makes it work for any ordered type.
3: Implement retry logic with exponential backoff using Future.
Bad answer: Call the function in a loop until it works.
Good answer: def retry[A](n: Int, delay: Long)(f: => Future[A])(implicit ec: ExecutionContext): Future[A] = f.recoverWith { case _ if n > 0 => after(delay)(retry(n – 1, delay * 2)(f)) }. Each retry doubles the wait.
4: Write a function that validates multiple fields using Either.
Bad answer: Use try-catch for each field separately.
Good answer: def validate(name: String, age: Int): Either[String, User] = for { n <- validateName(name); a <- validateAge(age) } yield User(n, a). Each step returns Either and the chain short-circuits on the first Left.
5: Implement a simple state machine using sealed traits.
Bad answer: Use a var with string labels like state1 and state2.
Good answer: Define sealed trait State with case objects for each state. Write a transition function (State, Event) => State using pattern matching. The compiler ensures exhaustive coverage of all state-event combinations.
6: Implement a thread-safe memoisation function.
Answer: Use ConcurrentHashMap: def memo[A, B](f: A => B): A => B = { val cache = new ConcurrentHashMap[A, B](); a => cache.computeIfAbsent(a, f(_)) }.
7: Write a function that partitions a list into sublists of size n.
Answer: def grouped(xs: List[Int], n: Int): List[List[Int]] = xs.grouped(n).toList. The standard grouped method handles it.
8: Implement binary search on a sorted Vector.
Answer: Use a tail-recursive helper with low/high indices. Compare the midpoint value and narrow the range until found or exhausted.
9: Write a function to deeply merge two nested Maps.
Answer: Recursively merge keys, combining values when both are Maps and preferring the second value otherwise.
10: Implement the Sieve of Eratosthenes using LazyList.
Answer: def sieve(s: LazyList[Int]): LazyList[Int] = s.head #:: sieve(s.tail.filter(_ % s.head != 0)). Start with LazyList.from(2).
11: Write a function that merges two sorted iterators into one.
Answer: Use BufferedIterator, compare heads, and advance the smaller one until both are exhausted.
12: Implement a generic fold for a binary tree.
Answer: Define sealed trait Tree[+A] with Leaf and Branch. def fold[A,B](t: Tree[A])(f: A => B)(g: (B,B) => B): B pattern-matches and recurses on branches.
13: Write a function that converts a Map to a case class using a type class.
Answer: Define FromMap[A] with def from(m: Map[String, Any]): Either[String, A]. Provide instances for specific case classes that extract and validate each field.
14: Implement a circuit breaker pattern.
Answer: Track failures in Closed, Open, or HalfOpen state. After a failure threshold open the circuit. After a timeout allow a single test call to determine recovery.
15: Write a function that collects results from a list of Futures, tolerating failures.
Answer: Map each Future to Future[Either[Throwable, A]] via .map(Right(_)).recover { case e => Left(e) }, then use Future.sequence.
16: Implement a simple publish-subscribe event bus.
Answer: Use a mutable map of event type to list of callbacks. Publish invokes all registered callbacks for that type.
17: Write a function that reads a file and returns Either[Throwable, String].
Answer: Use scala.util.Using(Source.fromFile(path))(_.mkString).toEither to safely read and auto-close the resource.
18: Implement a token-bucket rate limiter.
Answer: Maintain a count and timestamp. On each call calculate elapsed time, add tokens proportionally, and allow the call only if tokens are available.
19: Write a function to serialize a case class to a JSON string without a library.
Answer: Use productElementNames and productIterator to extract field names and values, then build a JSON string. Works for simple flat case classes.
20: Implement tail-recursive in-order tree traversal.
Answer: Use an explicit stack (List) instead of the call stack. Push nodes and descend left, then process and go right.
21: Write a function that safely parses a config string into a Map.
Answer: Split by lines and the = delimiter, trim keys and values, skip malformed lines, and return Map[String, String].
22: Implement a simple LRU cache with a maximum size.
Answer: Combine a Map with a queue tracking access order. On access move the key to the back. On insert evict the front when full.
23: Write a concurrent pipeline that processes items through multiple stages.
Answer: Chain Futures with flatMap where each stage transforms the data. Use separate ExecutionContexts for blocking stages.
24: Implement a retry combinator for IO in Cats Effect.
Answer: def retryN[A](io: IO[A], n: Int): IO[A] = io.handleErrorWith { e => if (n > 0) retryN(io, n – 1) else IO.raiseError(e) }.
25: Write a function that computes the Levenshtein distance between two strings.
Answer: Use dynamic programming with a 2D array. Compare characters and take the minimum of insert, delete, and substitute operations at each cell.
Practice-based Middle Scala Developer Interview Questions
These questions test practical experience with build tools, testing, deployment, and real-world project decisions that middle developers face regularly.
1: How do you set up a multi-module sbt project?
Bad answer: Create separate projects and copy code between them.
Good answer: Define a root project with .aggregate(module1, module2) and use .dependsOn for inter-module dependencies. Each module has its own src directory but shares a single build.sbt file.
2: How do you connect to a database in a Scala application?
Bad answer: Use raw JDBC with string concatenation for queries.
Good answer: Use a library like Doobie (functional) or Slick (FRM). Define typed queries, manage connections with a transactor or pool (HikariCP), and return results wrapped in IO or Future for safe resource handling.
3: How do you build a REST API in Scala?
Bad answer: Parse HTTP requests manually and write response strings.
Good answer: Use http4s (functional) or Play Framework (MVC). Define routes with typed endpoints, use JSON codecs (Circe, Play JSON) for serialisation, and run the server with a Cats Effect or Akka runtime.
4: How do you set up CI/CD for a Scala project?
Bad answer: Compile on my laptop and deploy manually.
Good answer: Use GitHub Actions or GitLab CI with sbt Docker images. Define stages for compile, test, and format check (scalafmt). Cache .ivy2 and .sbt directories to speed up builds, and add a publish step for releases.
5: How do you containerise a Scala application with Docker?
Bad answer: Copy the entire IDE project folder into a Docker image.
Good answer: Use sbt-native-packager to generate a Docker image with sbt Docker/publishLocal. It creates a minimal JRE-based image with the assembled JAR and a proper entry point.
6: What sbt plugins do you commonly use?
Answer: sbt-assembly for fat JARs, sbt-native-packager for Docker/deb/rpm, sbt-scalafmt for formatting, sbt-scoverage for coverage, and sbt-revolver for hot reloading during development.
7: How do you choose between compile-time and runtime dependency injection?
Answer: Compile-time DI (MacWire, manual wiring) catches missing dependencies at compile time. Runtime DI (Guice) is more flexible but errors show only at startup. Prefer compile-time for Scala projects.
8: What logging practices do you follow in Scala?
Answer: Use SLF4J with Logback. Log at appropriate levels. Use structured logging with MDC for request tracing. Avoid string concatenation in log messages.
9: How do you manage configuration?
Answer: Use Typesafe Config for HOCON or PureConfig for automatic case class mapping. Separate environment-specific settings through overrides and environment variables.
10: What is property-based testing and how do you use it?
Answer: Property-based testing (ScalaCheck) generates random inputs and verifies that properties hold for all of them. It finds edge cases that unit tests miss.
11: How do you approach integration testing?
Answer: Use testcontainers-scala to spin up Docker containers for databases and services. Write tests that exercise real interactions and clean up automatically.
12: What is JMH and how do you use it?
Answer: JMH (Java Microbenchmark Harness) measures method performance accurately. Use sbt-jmh, annotate methods with @Benchmark, and run with controlled warm-up and iterations.
13: How do you measure code coverage?
Answer: Use sbt-scoverage. Run sbt coverage test coverageReport to generate HTML and XML reports with line and branch coverage percentages.
14: What are the key steps in migrating from Scala 2 to Scala 3?
Answer: Start with the -source:3.0-migration flag. Address implicit conversions, replace procedure syntax, update macros, and switch to given, using, extension, and enum.
15: How do you cross-build a library for multiple Scala versions?
Answer: Set crossScalaVersions in build.sbt and run sbt +test to compile and test against each version.
Tricky Middle Scala Developer Interview Questions
These questions probe deeper understanding and common pitfalls. They test areas where experienced developers sometimes stumble and form a bridge towards expert Scala interview questions.
1: How does type erasure affect pattern matching on generic types?
Bad answer: Scala preserves generic types at runtime, so matching works.
Good answer: The JVM erases type parameters at runtime. Matching on List[Int] vs List[String] does not work because both are just List at runtime. Use ClassTag or TypeTag to preserve type information. The compiler warns about unchecked matches.
2: What is the diamond problem in trait linearization?
Bad answer: Scala does not allow multiple traits, so the diamond problem does not exist.
Good answer: When a class mixes in traits that share a common ancestor, Scala linearises right to left, removing duplicates. The method from the last trait in the linearization wins, and super calls follow the chain, avoiding ambiguity.
3: What causes ambiguous implicit errors?
Bad answer: Just add more implicits until the error goes away.
Good answer: Ambiguous implicits occur when two values of the same type are in scope with equal priority. Fix by placing one in a companion object (lower priority), using explicit import, or qualifying the implicit parameter.
4: Can lazy val initialisation cause deadlocks?
Bad answer: No, lazy val is always safe to use.
Good answer: In Scala 2, lazy val uses a synchronized block on the enclosing object. If two threads each hold a lock and wait for the other’s lazy val, a deadlock occurs. Scala 3 uses a safer initialisation scheme.
5: What are variance position errors and how do you fix them?
Bad answer: Variance errors are compiler bugs that should be ignored.
Good answer: A covariant type parameter (+A) cannot appear in contravariant positions such as method parameters. Fix by introducing a lower bound: def add[B >: A](b: B). The compiler enforces these rules to maintain type safety.
6: Why does Function1[-A, +B] use contravariance for input?
Answer: A function accepting Animal can replace one accepting Cat (wider input). A function returning Cat can replace one returning Animal (narrower output). This preserves Liskov substitutability.
7: Why is Future not referentially transparent?
Answer: Creating a Future immediately starts execution. Reusing val f = Future(…) differs from calling Future(…) twice because the first reuses the cached result while the second starts a new computation.
8: What issues can implicit widening conversions cause?
Answer: Widening conversions (Int to Long) trigger silently, leading to unexpected overloading resolution and numeric precision loss without compiler warnings.
9: Why can case objects cause issues with serialisation?
Answer: Case objects are singletons. Deserialisation creates a new instance, breaking reference equality (eq). Use readResolve to return the singleton instance.
10: What happens with circular lazy val dependencies?
Answer: If lazy val a depends on lazy val b and b depends on a, accessing either causes a StackOverflowError or returns null/0 depending on initialisation order.
Tips for Scala Interview Preparation for Middle Developers
Working through Scala coding practice questions and reviewing each middle Scala developer interview question in this guide is a strong foundation, but preparation extends beyond memorising answers.
- Practice explaining trade-offs, not just definitions. Interviewers expect middle developers to compare approaches and justify choices.
- Build a side project using an effect system such as Cats Effect or ZIO. Hands-on experience with IO, Resource, and fibres strengthens your answers significantly.
- Read the source code of libraries you use. Understanding how Circe, Doobie, or http4s implement type classes deepens your grasp of idiomatic Scala.
- Study the bad answers in this guide carefully. Recognising common misconceptions helps you avoid them under pressure.
- Review variance, implicits, and type bounds before the interview. These topics appear frequently and distinguish middle candidates from juniors.
- Practice whiteboard coding with algebraic data types and pattern matching. Most coding rounds at this level involve these constructs.
Technical Interview and Assessment for Middle Scala Developers
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Conclusion
Scala interviews at the middle level reward candidates who combine solid functional programming knowledge with the ability to discuss real-world trade-offs. Use these 100 questions to identify gaps, practise articulating your reasoning, and build the confidence to walk into any technical round prepared. Consistent practice with realistic problems is the most reliable way to demonstrate the depth that hiring teams expect from a mid-level Scala developer.
