Senior Data Integration Engineer

EPAM Systems; Turkey; On-site; TRY 5,923,000 - 8,885,000; Full time

Benefits offered by this job

Continuous upskilling

Private health insurance

Professional development support

Learning platform access

English courses

Job summary

EPAM Systems is seeking a Senior Data Integration Engineer to lead modern data integration and cloud-native pipeline initiatives. You will bridge source environments and analytical databases, collaborating with product, engineering, and architecture teams to ensure data accuracy and reliability.

The role focuses on scalable ETL/ELT design, workflow orchestration with Airflow and cloud schedulers, and building data warehouse/lakehouse layers using Snowflake, Azure Synapse, and Redshift.

Qualifications

• 5+ years of hands-on experience in data engineering, data warehousing, database design, and end-to-end data integration.
• Advanced knowledge of Cloud Integration tools such as Azure Data Factory (ADF), AWS Glue, or GCP Dataflow.
• Proficiency in workflow orchestrators like Apache Airflow and exposure to CDC or real-time streaming tools (e.g., Kafka, Debezium).
• Strong production-level coding skills in SQL, Python, and PySpark / Apache Spark.
• Experience with high-performance databases and cloud-native systems (e.g., Snowflake, ClickHouse, PostgreSQL, MS SQL Server, or Azure Synapse).
• Master-level understanding of data modeling practices (OLAP, OLTP, Star/Snowflake schemas, Delta Lake/Lakehouse patterns, and Data staging processes).
• Hands-on experience with version control (Git) and building automated deployment pipelines for data products.
• Proven ability to articulate complex technical ideas clearly to both business stakeholders and developers.
• Fluency in English (Upper-Intermediate level or higher).

Responsibilities

• Design, build, and optimize scalable batch and near-real-time ETL/ELT pipelines using Python, PySpark, SQL, and cloud engines.
• Develop and manage complex workflow orchestrations and automate ingestion routines to minimize manual operations.
• Design and implement modern data warehouse/lakehouse layers (Snowflake, Synapse, Redshift) with partitioning and SCD type 2.
• Establish data quality checks and validation with dbt, Soda, or PySpark tests.
• Collaborate with product owners and architects to define data requirements and STTM mappings.
• Maintain a clean code repository; lead code reviews and configure CI/CD pipelines with containerization.
• Deliver technical specs, metadata lineage, diagrams, and data dictionaries.

Skills

Python

SQL

PySpark

Data modeling

ETL/ELT design

Cloud data engineering

CI/CD

Communication

Tools

Airflow

Snowflake

Azure Synapse

Redshift

dbt

Docker

Kubernetes

Job description

We are seeking a highly skilled, solution-oriented Senior Data Integration Engineer with deep expertise in modern data engineering, cloud-native architectures, and robust pipeline development.

In this role, you will be a senior technical driver in creating, optimizing, and modernizing advanced data integration systems. You will collaborate closely with product, engineering, and architecture teams to bridge raw source environments and analytical databases. If you excel in cloud ecosystems, thrive on automating complex data workflows, and value precision, reliability, and data quality above all, we encourage you to apply!

Responsibilities

• Design, build, and optimize scalable, reliable batch and near-real-time ETL/ELT pipelines using Python, PySpark, SQL, and modern cloud integration engines
• Develop and manage complex workflow orchestrations (using Apache Airflow or cloud native schedulers) and automate ingestion routines to minimize manual operations
• Design and implement modern data warehouse/lakehouse layers (using Snowflake, ClickHouse, Azure Synapse, or Redshift), establishing optimal partitioning, indexing, and Slowly Changing Dimension (SCD Type 2) patterns
• Establish rigorous data quality checks and validation frameworks utilizing tools like dbt (data build tool), Soda, or customized PySpark testing suites
• Work closely with product owners, business analysts, and systems architects to define data requirements, analyze technical constraints, design Source-to-Target Mappings (STTM), and make critical architectural decisions
• Maintain a clean, modular code repository. Lead code reviews, enforce engineering standards, and configure robust CI/CD pipelines (Azure DevOps, GitLab CI, or GitHub Actions) with Docker containers
• Deliver comprehensive, clear technical specs, metadata lineage documentation, architectural diagrams, and data dictionaries

Requirements

• 5+ years of hands-on experience in data engineering, data warehousing, database design, and end-to-end data integration
• Advanced knowledge of Cloud Integration tools such as Azure Data Factory (ADF), AWS Glue, or GCP Dataflow
• Proficiency in workflow orchestrators like Apache Airflow and exposure to CDC (Change Data Capture) or real-time streaming tools (e.g., Kafka, Debezium)
• Strong production-level coding skills in SQL (advanced optimization/stored procedures), Python, and PySpark / Apache Spark
• Experience working with high-performance databases and cloud-native systems (e.g., Snowflake, ClickHouse, PostgreSQL, MS SQL Server, or Azure Synapse)
• Master-level understanding of data modeling practices (OLAP, OLTP, Star/Snowflake schemas, Delta Lake/Lakehouse patterns, and Data staging processes)
• Hands-on experience with version control (Git) and building automated deployment pipelines (CI/CD) for data products
• Proven ability to articulate complex technical ideas clearly to both business stakeholders and developers
• Fluency in English (Upper-Intermediate level or higher)

Nice to have

• Deep knowledge of dbt (data build tool) and schema validation practices
• Experience using Docker or Kubernetes to package and deploy data applicationsExperience building lightweight, serverless ingestion services (e.g., using AWS Lambda / Azure Functions and RESTful APIs)

We offer

• CONTINUOUS UPSKILLING, LEARNING & DEVELOPMENT
  • Diversity of tasks and projects
  • Assessment center for objective review of competency level
  • Personal development plan
  • Mentoring programs and leadership development
  • Certification and professional development support
  • Access to learning platforms including more than 2,500 internal courses
  • English courses taught by certified teachers
• CORPORATE BENEFITS
  • Extra leave days
  • Referral bonuses
• COMPENSATION PACKAGE
  • Competitive compensation paid in USD
  • Regular salary and performance reviews
• MEDICAL & HEALTHCARE
  • Private health insurance
  • Well-being events
• WORKING ENVIRONMENT
  • Recreation areas and kitchens
  • Tea, coffee and snacks
  • Sports equipment and game consoles
  • IT Equipment
  • Microsoft’s Software Assurance Home Use Program (HUP)

EPAM is global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.