Hire the Best Scala Developers

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Ian S.

Nairobi, Kenya

$40/hr
5.0
22 jobs

I am a Software Engineer with over a decade of experience in Backend development, CRUD, Web, RESTful APIs, Unit Testing, and Scala. I am dedicated to creating scalable applications that help my clients stand out. I am currently seeking challenging projects and opportunities to utilize my problem-solving skills and experience to help businesses achieve their goals in both technology and business domains. If you value well-designed, impactful software systems delivered efficiently, I am the right person for you. Technologies and platforms I am proficient in include Scala, Play Framework, Akka, RDBMS, NoSQL, ZIO, HTTP4S, Cats Effect, Monix, Kafka, AWS, Apache Spark, RAG, Gen AI, LLMs, Claude, Codex, and Functional Programming.

  • Scala
  • SQL
  • Akka-HTTP
  • Amazon ECS
  • Apache Kafka
  • API Development
  • Functional Programming
  • Continuous Integration
  • GraphQL
  • Akka
  • Apache Spark
  • Microservice
  • Slick
  • Docker
  • Play Framework
  • Apache Cassandra
  • Python
  • Java
  • TypeScript
  • Node.js
Jayant C.

Gandhinagar, India

$20/hr
4.9
31 jobs

āœ… Top Rated Plus | 100% JSS | 4x Certified (AWS SA Pro, GCP Pro Architect, Snowflake) | BITS Pilani MTech Data Science | Full Stack Developer & Data Engineer | React, Python, Node.js, Spark | $20K+ earned | 1,845+ hours I build full-stack web applications and data engineering systems that go to production, not to demo day. SaaS MVPs, Spark-based ETL pipelines, cloud architecture on AWS and GCP, I handle both the application layer and the data infrastructure behind it. šŸ”¹ Full-Stack SaaS & Web Application Development React, Next.js, Node.js, and Python backends for SaaS platforms, dashboards, internal tools, and customer-facing apps. MVP to production on AWS/GCP with CI/CD, automated testing, and monitoring from day one. 19 Upwork contracts delivered with structured milestones. šŸ”¹ Data Engineering & ETL Pipeline Architecture End-to-end data pipeline design with Apache Spark, PySpark, Scala, Snowflake, and Airflow. Batch and streaming ETL processing millions of records per run. Data lake architecture, warehouse modeling, analytics-ready output layers. 8+ years building production Spark + Cassandra systems at enterprise scale. šŸ”¹ Cloud Architecture & Infrastructure (AWS + GCP) 4 cloud architecture projects on Upwork, all rated 5.0. $2,300 CloudStack design. AWS architecture advisory. EC2, Lambda, S3, RDS, EMR, Redshift on AWS. BigQuery, Dataflow, Cloud Functions on GCP. Terraform for IaC, Docker and Kubernetes for orchestration, zero-downtime deployments. šŸ”¹ API Development & Backend Systems REST API and GraphQL backends with Node.js, NestJS, FastAPI, and Django. Microservices, Redis caching, WebSocket integrations, Stripe payment APIs, OAuth/JWT authentication. Backend services handling concurrent users at production scale. šŸ”¹ Database Design & Data Modeling PostgreSQL, MongoDB, MySQL, Cassandra, DynamoDB, Redis. Schema design, query tuning, indexing, partitioning. Star and snowflake schemas, slowly changing dimensions, SQL optimization for analytics. Architecture decisions balancing performance, throughput, and cost. šŸ”¹ AI Integration & Intelligent Applications OpenAI API, Hugging Face, NLP pipelines, chatbot systems, text extraction and summarization. Delivered NLP processing on Upwork. AI-powered features built into SaaS products as production features, not standalone experiments. šŸ”¹ Real-Time Processing & Event-Driven Systems Kafka for event-driven architectures, change data capture, WebSocket dashboards, streaming pipelines for near-real-time analytics. Application events connected to data warehouse layers. šŸ”¹ Frontend Performance & TypeScript Engineering React and Next.js with SSR/SSG for SEO-friendly rendering. TypeScript full stack. Core Web Vitals optimization, Tailwind CSS, responsive design. Fast-loading frontends that rank and convert. šŸ”¹ DevOps, CI/CD & Production Systems Docker, Kubernetes, Terraform, GitHub Actions, GitLab CI. Serverless with AWS Lambda and GCP Cloud Functions. Monitoring, logging, alerting for production. Zero-downtime deployment strategies. šŸ”¹ Technical Consulting & Architecture Advisory TypeScript and AWS Lambda tutor on Upwork, rated 5.0 over 13 hours. Cloud migration advisory, system design review, code audits, performance optimization, engineering mentorship. šŸ“Š AWS Solutions Architect Professional + Associate (Dec 2026) | GCP Pro Cloud Architect (Jul 2026) | Snowflake Core (Jan 2026) šŸ“Š MTech Data Science, BITS Pilani, ranked top 5 engineering institutions in India šŸ“Š 19 contracts, 100% JSS, Top Rated Plus, 1,845+ hours tracked, $20K+ earned šŸ“Š "Jay's expertise brought the architecture design to life in ways I hadn't imagined" (5.0 rated) šŸ“Š 8+ years: React, Node.js, Python, Java, Scala across SaaS, healthcare, fintech, enterprise → Day 1: Requirements call + architecture proposal with tech stack rationale → Week 1: Sprint development, daily Loom/Slack updates, working code shipped → Ongoing: Weekly demos, priority reviews, transparent tracking, full documentation → Delivery: Documented code, CI/CD configured, deployment guide, 2-week post-launch support Full Stack: React, Next.js, Node.js, NestJS, Express, TypeScript, JavaScript, Python, FastAPI, Django Data: Apache Spark, PySpark, Scala, Snowflake, Airflow, Kafka, ETL, dbt, SQL, BigQuery Cloud: AWS (Lambda, EC2, S3, RDS, EMR, Redshift), GCP (BigQuery, Dataflow), Docker, Kubernetes, Terraform DB: PostgreSQL, MongoDB, MySQL, Redis, Cassandra, DynamoDB, Supabase AI: OpenAI API, Hugging Face, NLP, LLM Integration, TensorFlow, PyTorch šŸ’¬ Message me with your project scope or data challenge. I respond within 4 hours with a free assessment and can start within 48 hours.

  • Scala
  • Java
  • Python
  • React
  • Node.js
  • Full-Stack Development
  • Data Engineering
  • TypeScript
  • API Integration
  • PostgreSQL
  • Next.js
  • Apache Spark
  • AWS Lambda
  • NestJS Development
  • Generative AI
  • Snowflake
  • DevOps
  • Google Cloud Platform
  • ETL
  • SQL
Joshua A.

Ado Odo, Nigeria

$5/hr
5.0
3 jobs

š—œ š——š—¢š—”'š—§ š—š—Øš—¦š—§ š—–š—„š—˜š—”š—§š—˜ š—”š—œ š—©š—œš——š—˜š—¢š—¦. š—œ š—–š—„š—˜š—”š—§š—˜ š—Øš—šš—– š—”š——š—¦, š—”š—œ š—”š—©š—”š—§š—”š—„ š—©š—œš——š—˜š—¢š—¦ & š—–š—¢š— š— š—˜š—„š—–š—œš—”š—Ÿ š—–š—¢š—”š—§š—˜š—”š—§ š—§š—›š—”š—§ š——š—„š—œš—©š—˜š—¦ š—„š—˜š—¦š—Øš—Ÿš—§š—¦. If you're looking for an AI Video Creator who can produce high-converting UGC ads, AI avatar videos, ecommerce commercials, product videos, and short-form content that stops the scroll, you're in the right place. I help ecommerce brands, Shopify stores, SaaS companies, agencies, coaches, and creators turn ideas into engaging AI-powered content designed to increase visibility, engagement, and conversions. šŸŽÆ SERVICES šŸ”¹ AI UGC VIDEO ADS • AI UGC Ads • Product Demo Videos • Product Review Videos • Testimonial Style Ads • Selfie Style UGC Content • TikTok Video Ads • Meta & Facebook Ads • Instagram Reels • YouTube Shorts • Direct Response Video Ads • Ecommerce Product Videos • Shopify Video Ads šŸ”¹ AI AVATAR VIDEOS • HeyGen Videos • AI Spokesperson Videos • Talking Head Videos • AI Influencer Videos • Corporate Training Videos • Course Videos • Educational Content • Multilingual AI Videos • Lip-Sync Videos • AI Voiceover Content šŸ”¹ AI VIDEO CREATION • Text-to-Video Production • Image-to-Video Production • AI Commercial Videos • Product Marketing Videos • SaaS Explainer Videos • Brand Storytelling Videos • Social Media Content • Promotional Videos • AI Music Videos • Cinematic Short-Form Videos šŸ”¹ SHORT-FORM CONTENT • TikTok Content • Instagram Reels • YouTube Shorts • Viral Video Editing • Hook-Based Content • Retention-Focused Editing • Social Media Marketing Videos āš™ļø TOOLS I USE AI Video: Seedance 2.0, Higgsfield, Veo 3, Kling AI, Runway, Pika Labs, Luma AI AI Avatars: HeyGen, Synthesia, Colossyan AI Voice: ElevenLabs, PlayHT AI Images: Midjourney, Flux, Leonardo AI, GPT Image, Nano Banana Pro Editing: Adobe Premiere Pro, After Effects, DaVinci Resolve, CapCut Pro 🧠 WHY CLIENTS WORK WITH ME Most creators focus on generating videos. I focus on creating content that performs. I combine: • UGC Ad Strategy • Direct Response Marketing • Conversion Psychology • Hook Engineering • Retention Editing • AI Prompt Engineering • Creative Storytelling Every project is built to: āœ” Capture Attention Fast āœ” Increase Watch Time āœ” Improve Engagement āœ” Generate More Clicks āœ” Drive More Sales āœ” Strengthen Brand Awareness šŸ’¼ WHO I WORK WITH • Ecommerce Brands • Shopify Stores • SaaS Companies • Marketing Agencies • Course Creators • Coaches & Consultants • Beauty Brands • Health & Wellness Brands • Personal Brands • Content Creators If you're looking for cheap content, I'm probably not the right fit. If you're looking for premium AI video content designed to grow your brand and improve results, let's talk. šŸ“© SEND ME A MESSAGE WITH: • Your product or service • Your target audience • Your platform (TikTok, Meta, Instagram, YouTube) • Your goals I'll help you build a content system that combines AI video, UGC, avatars, and performance marketing to help your brand stand out. KEYWORDS AI Video Creation AI Video Generation AI Content Creation AI Filmmaking AI Video Editing AI Animation Generative AI AI Storytelling AI Commercial Production AI Marketing Content AI Video Creation AI Video Generation AI Content Creation AI Filmmaking AI Video Editing AI Animation Generative AI AI Storytelling AI Commercial Production AI Marketing Content UGC Video Creation AI UGC Videos UGC Advertising Creator Style Ads User Generated Content TikTok UGC Ads Instagram UGC Content AI Influencer Marketing Product Demo Videos Direct Response Advertising TikTok Video Ads Instagram Reels YouTube Shorts Short Form Video Viral Video Creation Social Media Videos Vertical Video Production Reels Video Editing Video Marketing Performance Creative Ecommerce Video Ads Shopify Video Ads Amazon Product Videos Product Advertising Product Marketing Product Launch Videos DTC Advertising Conversion Focused Ads Sales Video Creation Video Sales Letters Seedance 2.0 Higgsfield AI GPT Image GPT Image 2 Kling AI Veo 3 Google Veo Sora AI Runway ML Pika Labs Commercial Video Production Brand Storytelling Cinematic Video Production Video Commercials Luxury Brand Advertising Creative Direction Visual Storytelling Digital Advertising Branded Content Creative Production Motion Graphics 3D Animation Product Animation Character Animation Cinematic Animation AI Motion Design Visual Effects Video Compositing Storyboard Creation Scene Development Performance Marketing Meta Ads Creative Facebook Video Ads Instagram Ads TikTok Marketing Creative Strategy Ad Creative Testing Conversion Optimization Customer Acquisition Marketing Automation Real Estate Video Luxury Real Estate Marketing Skincare Advertising Beauty Product Videos Fashion Marketing Travel Content Creation Tourism Marketing Fitness Advertising Supplement Marketing SaaS Marketing Prompt Engineering AI Prompt Design Creative AI Workflows Character Consistency Image to Video Cinematic Editing AI Avatars

  • AI Content Creation
  • AI Video Generation
  • AI Video Generator
  • Video Editing
  • Video Editing & Production
  • Short Video Ad
  • Video Ad
  • Social Media Video
  • TikTok Video
  • YouTube Video
  • Synthesia
  • Explainer Video
  • AI Image Generation
  • AI Image Generator
  • AI Image Editing
  • Audio Production
  • AI Audio Generator
  • AI Audio Generation
  • UGC
  • Adobe Premiere Pro
Huanqing Z.

Shenzhen, China

$25/hr
4.9
56 jobs

I'm Huanqing Zhu, and you can call me Fusion. With over 10 years of hands-on Java development experience—including 6 years dedicated to big data processing and visualization—I’ve built my expertise by staying rooted in frontline coding, even as my responsibilities have grown. A key pillar of my technical toolkit is ā€Œ6 years of production-grade Rust development experienceā€Œ, complemented by proficiency in Java, Scala, JavaScript, HTML5, and a full stack of big data and cloud-native technologies: Apache Spark, Hadoop, Hive, Flume, HBase, Storm, Kafka, DataX, ECharts, Docker, Kubernetes, and Linux. What sets me apart is that I’ve never stepped away from writing production code, even as I’ve taken on leadership and architectural roles: As a ā€Œhands-on Big Data Developerā€Œ, I’ve built robust data ingestion utilities (including the open-source DataXServer on GitHub) and real-time page click analytics systems, directly coding pipelines to pull data from RDBMS, NoSQL databases, and file storage into production environments. As a ā€ŒBig Data Architectā€Œ, I’ve led platform design while still contributing core code, using Hadoop, Spark, Flink, and ElasticSearch to build scalable data infrastructure—no abstract planning here; I’ve written the critical components that power these systems. As a ā€ŒRust Specialistā€Œ, my 6 years of experience spans building high-performance, low-latency systems. I’ve used Rust to optimize data processing pipelines, cut latency by up to 40% in high-throughput scenarios, and deliver systems that run 24/7 with zero critical errors. As a ā€ŒTeam Leaderā€Œ, I’ve managed full-stack teams (Java, front-end, QA, operations) while still pairing with developers on complex code reviews and contributing to high-priority features, ensuring I stay connected to the day-to-day challenges of software delivery. I also bring deep experience in microservices architecture and cloud-native containerization, and my cross-language expertise lets me bridge gaps between Java-based enterprise systems and Rust-powered high-performance components. If you’re looking for a professional who combines strategic vision with the grit to deliver production-ready code—someone who can architect a system, and write the Rust or Java code that makes it run—I’m the candidate for you. Thank you for reviewing my profile. I’m eager to discuss how my hands-on experience can add value to your team.

  • Scala
  • Apache Hadoop
  • Apache Spark
  • Apache Kafka
  • Apache Flink
  • Spring Boot
  • Rust
  • D3.js
  • OpenLayers
  • Docker
  • Web Development
  • Elasticsearch
  • JavaScript
  • Java
  • React
Romit S.

Pune, India

$45/hr
5.0
15 jobs

Hands on Data architect & Lead data engineer, with 12+ years of experience in designing & building end to end high velocity, high volume peta byte real time & batch data platforms from scratch on clouds & on-prem. Kubernetes native development from the beginnig. I develop distributed & scalable back-end systems using using languages like goLang, Rust & python. Lately Started working on integration of AI, RAG, MCP Servers & MLops Platforms into data platforms. Developed self hosted llms applications using Ollama and llm observability using langfuse. Mordenize existing data platforms with AI first approach. Hybrid semantic mapping layers or unstructured and structured data using heuristics, memory and LLMs. Built & worked on peta byte scale streaming, batch data & AI platforms in top companies. An open source contributor to data technologies & products like Airbyte etc. Love working on database internals, performance and optimizations. I have experience working with telemetry data, payments data, video data, sports data, eCommerce data & affiliate marketing data, logs data, clickstream data. Skill Set: Big Data Technologies: Spark, Kafka, Flink, Presto, Dremio, Hudi, Deltalake Data warehouses: Snowflake, Druid, Clickhouse, Redshift, SingleStore(Memsql), Quest Databases: Postgres, Mysql, Cassandra, DynamoDB, DuckDB Programming languages: Golang, Python, Rust, Scala, Java Visualization: Tableau, Apache Superset, Zoomdata Data Technologies - Airbyte, Fivetran, Dagster, Airflow, Nifi, Kubeflow, ElasticSearch, OpenSearch Platforms: Databricks, Snowflake, Cloudera, Supabase, Aiven Ops: Kubernetes, Docker Cloud: AWS, GCP, Azure

  • Apache Cassandra
  • Apache Spark
  • Apache Kafka
  • Data Engineering
  • Snowflake
  • Amazon Web Services
  • Big Data
  • Golang
  • PostgreSQL
  • Streaming Platform
  • Data Lake
  • Machine Learning
  • ClickHouse
  • Apache Druid
  • LangChain
  • AI Platform
  • Real Time Stream Processing
  • Apache Flink
  • Rust
Fahad S.

Lahore, Pakistan

$50/hr
5.0
86 jobs

A working demo and a system that survives production are two very different things. I build the second kind. Over a decade of backend engineering and 70+ completed projects on Upwork. I run Datum Brain, a software and AI engineering company, so you get one senior engineer accountable end to end, with a team behind him when the work needs it. We ship Go microservices, data pipelines, and LLM systems for FinTech, SaaS, EdTech, and AdTech clients. Recent work: šŸ›” Real-time ad fraud detection (TrueAudience) High-concurrency Go backend that scores ad traffic to catch bots before advertisers pay. 80M+ events, under 20ms decisions. Go, TimescaleDB, real-time pipelines. šŸ¦ Go microservices for an EMI and payments platform (Zolvat) Ledger logic, payment flows, and service orchestration for an installment payments platform. Go, microservices, PostgreSQL. šŸŽ„ WebRTC proctoring infrastructure (Meazure / Examity) Real-time media and session orchestration for thousands of concurrent exam sessions at one of the largest US proctoring providers. Go, WebRTC, LiveKit, NATS. šŸ“Š Big data pipeline optimization (Nike) Cut processing time and compute cost on large PySpark workloads. PySpark, AWS. šŸ“„ Document intelligence platform (Centrum AI) OCR and RAG pipeline that turns unstructured documents into structured, queryable data with human review. Python, FastAPI, LangChain, RAG. What I work with: Backend: Go, Python, FastAPI, gRPC, REST, PostgreSQL, TimescaleDB, Redis, NATS, Kafka Data: PySpark, ETL pipelines, data quality frameworks, AWS, GCP Real-time: WebRTC, LiveKit, event streaming, high-concurrency systems AI and LLM: LangChain, LangGraph, RAG, multi-agent systems, OpenAI, Claude, evals Infra: Docker, Kubernetes, CI/CD, nginx How I work: I scope before I quote, so you know what you are getting and when. I flag risks early instead of at the deadline. Production-ready means tested, documented, monitored, and handed over properly. Good fit if you need something that runs in production and not a proof of concept, you want one senior engineer accountable end to end, and you value clear communication and honest scoping. Not a fit if you are shopping purely on hourly rate, or the spec changes daily and nobody owns decisions. If your backend needs to handle real load, or your data or AI work needs to go from demo to product, send me a message.

  • Python
  • Apache Spark
  • Golang
  • Large Language Model
  • Generative AI
  • Artificial Intelligence
  • OpenAI API
  • AI Bot
  • Big Data
  • ETL Pipeline
  • Microservice
  • Web Scraping

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Scala: A Hybrid Language for Big Data

What is Scala?

Scala is a highly scalable general purpose programming language that combines aspects of both object-oriented and functional programming. It’s become increasingly important in the world of data science, rivaling more established languages like Java and Python. One of the main drivers of Scala’s rise to prominence has been the explosive growth of Apache Spark (which is written in Scala), giving Scala a well-earned reputation as a powerful language for data processing, machine learning, and streaming analytics.

Powerful and General Purpose

Scala is designed to be much more concise and expressive. This does give it a steeper learning curve than Java, but for many developers, the trade off is well worth it. Still, the Java legacy is clear in many of Scala’s attributes, from its strong OOP support, to its curly brace syntax, to its high level of interoperability with Java libraries. What’s more, Scala’s source code is written to be compiled to Java bytecode and then run on the Java Virtual Machine, making it highly portable and safe. This gives Scala a wide-range of potential applications. Its Java compatibility makes it well suited to developing for Android, and its ability to compile to Javascript means Scala can even be used to write web apps. If you’re an object-oriented programmer who has no interest in learning functional programming, you can still pick up Scala and take advantage of Java’s many advantages (its rich libraries and the Java Virtual Machine) all while writing less boilerplate. 

Combining Functional And Object-Oriented Programming

One of Scala’s major advantages is its support for both object-oriented and functional programming. Both approaches aim to create readable, bug-free code, but they go about it in very different ways. Where object-oriented programming combines data structures with the actions you want to perform on them, functional programming keeps both separate.

Each approach has its advantages. For many people, the object-oriented paradigm makes intuitive sense, and combining behaviors with the data structures they’ll interact with can make it easy to figure out what’s going on in an unfamiliar codebase. At the same time, functional programming’s preference for cleanly separated and immutable data structures and discrete behaviors often allows you to do more with less code.

What to Look for in a Scala Developer

As with any developer role, the exact skills and experience you want will depend on your project and business goals. When looking for a Scala developer, it’s important to not only gauge their skills with the language, but also whether they’re able to learn quickly and build resilient systems. Experience with testing and program design are invaluable. Beyond those skills, here are some specific technologies and paradigms to look for in a Scala developer:

  • Object-oriented programming
  • The Java Virtual Machine
  • Tools of statistical analysis
  • Distributed file storage systems (like HDFS)
  • SQL and relational database management systems

Scala Interview Questions

Scala is a high-level language that combines the best of both worlds: object-oriented programming (OOP) and functional programming (FP). By treating functions as first-class citizens and embracing static types, Scala encourages developers to write safer code. Support for Java Virtual Machine (JVM) and JavaScript runtimes give a developer access to a wide variety of libraries for enhanced programmer productivity.

1. What are the advantages of using Scala?

Scala was created to enable programmers to use OOP and FP together: It brings OOP concepts such as first-class modules, dot syntax, and first-class type classes/instances together with FP concepts such as higher order functions and pattern matching.

Other advantages include type safety, a concise syntax, flexibility, and scalability. Built on top of the JVM, it is both compatible and interoperable with Java. Scala can perform many of the same tasks as Java with fewer lines of code without sacrificing readability.

2. What is functional programming?

FP is about composing code with pure functions (functions that always return the same result from the same input). This eliminates side effects associated with changing data or state. FP is generally characterized by:

  • Declarative programming model. You express the logic of a program’s structure and elements (what you want data to do) without having to describe its control flow (how it’s done).
  • Support for higher order functions. These are functions that take in one or more other functions and return a function as a result.
  • Immutable data and state.
  • Absence of side effects. Full absence of side effects is impossible (because software has to interact with the world), but functional languages either isolate side effects in a functional way (e.g., using monads in Haskell), or make usage of side effects explicit via language syntax (as in Clojure).

3. What is the difference between var, val, and def in Scala?

The var keyword lets you declare a variable, which is a changeable reference to a value. The val keyword lets you declare a constant, which is an immutable reference to a value. The def keyword lets you declare a function or a method.

4. Explain the difference between concurrency and parallelism.

It’s important to understand the difference between concurrency and parallelism when composing multithreaded programs. Concurrency is the ability to handle lots of things at once, such as a web server handling multiple requests. When one task starts, the program does not have to wait for it to finish before starting another task. In Scala, concurrency is handled with constructs called actors

Parallelism is a distinct concept that is more concerned with the actual simultaneous execution of said tasks, often in the context of breaking up a task into smaller subtasks that can be processed simultaneously across multiple threads and/or cores. Parallel collections, futures, and the Async library are all examples of parallelism in Scala.

5. What is a Scala future?

In Scala, a future is a placeholder for a value that may not yet exist. It makes it easier to write asynchronous, nonblocking, parallel code.

6. Explain higher order functions.

Higher order functions are simply functions that take other functions as parameters or return functions as results. The map, reduce, and filter functions are common examples—they form the bread and butter of modern-day data analytics.

7. Describe your experience working with Spark.

Written in Scala, Spark is a popular unified data analytics engine for large-scale data processing. This question is meant to be open-ended to give candidates a chance to show you how familiar they are with Spark. It’s generally a good sign if they mention RDDs (resilient distributed datasets) or lazy evaluation or if they have experience applying Spark to common big data projects such as:

8. Describe your experience working with Akka.

Akka is a library for creating fault-tolerant, concurrent, and distributed applications on the JVM inspired by the Reactive Manifesto. It uses actor-based concurrency to insulate developers from the details of dealing with low-level threads and locks. This open-ended question should give you insights into whether candidates have experience applying Akka to common big data projects such as those listed above.

9. Explain how pattern matching works in Scala.

Many languages, such as Java, use conditionals such as if/else or switch statements to check a series of possible conditions and take a different action for each condition based on the outcome—in other words, matching patterns. Pattern matching is a mechanism for checking a value against a pattern.

Example of matching on case classes in Scala:

abstract class Devicecase class Phone(model: String) extends Device { def screenOff = "Turning screen off"}case class Computer(model: String) extends Device { def screenSaverOn = "Turning screen saver on..."}
def goIdle(device: Device) = device match { case p: Phone => p.screenOff case c: Computer => c.screenSaverOn}

You can even use pattern matching with containers and container operations:

val list = List("a", "b", "c")val optional = list.headOption
optional match { case Some(s) => s.toUpperCase case None => "EMPTY"}
list match { case first :: _ => s"first element is $first" case _ => "list is empty"}

Scala makes it syntactically simple to compose blocks of cases that let you pattern match tuples, arrays, lists, classes, expressions, and more. Better still, pattern matching makes it easy to decompose object hierarchies, letting you access parameters of an object and process them on a case-by-case basis.

10. What is a monad?

A monad is an FP design pattern that manages complexity through composition. If you come from an object-oriented background, it’s helpful to think of a monad as a type amplifier (such as Nullable in C#) that follows a strict set of laws and supports certain operations (ā€œunitā€ and bindā€) that allow it to compose together functions which can operate on amplified types.

In Scala, this most often takes the form of data structures that use the higher order methods map and flatMap. To qualify as a monad, a type must satisfy these three laws:

1. Associativity

(m flatMap f) flatMap g == m flatMap (x => f(x) flatMap g)

2. Left Unit

unit (x) flatMap f == f(x)

3. Right Unit

m flatMap unit == m

Monads are an advanced topic which is best understood through category theory. It is enough if the interviewee is able to explain common examples of monads in Scala such as list, set, option, and generator.