Java Developer - Big Data

EPAM Systems; Polska; Hybrid; PLN 180,000 - 240,000; Full time

Job summary

EPAM Systems Inc is seeking a Java Developer with Big Data expertise to join a team building a next-generation valuation and risk management platform on Microsoft Azure. The role requires a hybrid work mode with 3 days in the office.

You will develop and maintain big data solutions, leveraging Apache Spark, Java, and Scala, while contributing to CI/CD pipelines and platform engineering on Azure. Collaboration across Front Office, Finance, and Risk is essential.

Qualifications

• 2+ years experience in software development with big data tech.
• Expertise in Apache Spark for big data processing.
• Proficiency in Java and Scala for production systems.
• Background in platform engineering on a major cloud provider (Azure).
• Experience with CI/CD pipelines (GitLab) and containerization.

Responsibilities

• Develop and maintain big data solutions using Apache Spark.
• Program complex production systems leveraging Java and Scala.
• Contribute to platform engineering initiatives on Microsoft Azure cloud infrastructure.
• Build, maintain, and enhance CI/CD pipelines using GitLab.
• Implement containerization strategies across development, build, and runtime environments.
• Deploy and orchestrate containerized workloads with Kubernetes.
• Collaborate with cross-functional teams to deliver platform capabilities.
• Ensure scalability, performance, and cost-efficiency of cloud PaaS components.
• Participate in architectural discussions and influence key technical decisions.

Skills

Big data

Apache Spark

Java

Scala

Azure cloud

Kubernetes

GitLab CI/CD

Python

Databricks

Terraform

Tools

GitLab

Terraform

Databricks

Azure CLI

Job description

We are seeking a skilled Java Developer with Big Data expertise to join our team working on a next-generation valuation and risk management platform built on Microsoft Azure. This platform delivers scalable, cost-efficient infrastructure through cloud PaaS components, featuring a single core platform with open architecture designed for change, itemized cost metrics, and automated data lineage. Shared across Front Office, Finance, and Risk functions, the platform improves regulatory compliance while providing a One-Platform / One-Experience approach that is fast to train, easy to operate, and helps retain talent. Please note that this role requires 3 days in the office in "flex-hybrid" mode.

Responsibilities

• Develop and maintain big data solutions using Apache Spark
• Program complex production systems leveraging Java and Scala
• Contribute to platform engineering initiatives on Microsoft Azure cloud infrastructure
• Build, maintain, and enhance CI/CD pipelines using modern cloud-friendly build systems like GitLab
• Implement containerization strategies across development, build, and runtime environments
• Deploy and orchestrate containerized workloads with Kubernetes
• Collaborate with cross-functional teams across Front Office, Finance, and Risk to deliver platform capabilities
• Ensure scalability, performance, and cost-efficiency of cloud PaaS components
• Participate in architectural discussions and influence key technical decisions

Requirements

• 2+ years of experience in software development with big data technologies
• Expertise in Apache Spark for big data processing
• Proficiency in Java and Scala for building complex production systems
• Background in platform engineering roles on a major cloud provider (ideally Microsoft Azure)
• Skills in developing and operating CI/CD pipelines using GitLab or similar cloud-friendly build systems
• Hands-on experience with containerization and Kubernetes across development, build, and runtime environments
• Ability to collaborate effectively within a large global team
• English proficiency at an Upper-Intermediate level (B2) or higher
• Nice to have Production experience with Terraform on a major public cloud provider (ideally Microsoft Azure)
• Experience with Databricks
• Knowledge of Python
• Understanding of information modeling, data structures, and algorithms
• Knowledge of testing, instrumentation, observability, and alerting tooling
• Background in technical architecture and low-level design
• Knowledge of Agile development and planning practices