Senior Data Integration Engineer

EPAM Systems

Remote · ArmeniaSalary not disclosedcontractVerified recentlyEPAM Systems Careers

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.

Responsibilities

Pipeline Architecture & Development
Design, build, and optimize scalable, reliable batch and near-real-time ETL/ELT pipelines using Python, PySpark, SQL, and modern cloud integration engines Orchestration & Automation
Develop and manage complex workflow orchestrations (using Apache Airflow or cloud native schedulers) and automate ingestion routines to minimize manual operations Data Modeling & Warehousing
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 Data Quality & Testing Integration: Establish rigorous data quality checks and validation frameworks…
Design: 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 Code Quality & DevOps
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 Technical Documentation
Deliver comprehensive, clear technical specs, metadata lineage documentation, architectural diagrams, and data dictionaries

Languages

Work format: Remote
Seniority: Senior
Posted: 7 Aug 2026 (3w ago)
Last verified: 28 Aug 2026

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Responsibilities

Pipeline Architecture & Development

Design, build, and optimize scalable, reliable batch and near-real-time ETL/ELT pipelines using Python, PySpark, SQL, and modern cloud integration engines Orchestration & Automation

Develop and manage complex workflow orchestrations (using Apache Airflow or cloud native schedulers) and automate ingestion routines to minimize manual operations Data Modeling & Warehousing

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 Data Quality & Testing Integration: Establish rigorous data quality checks and validation frameworks…

Design: 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 Code Quality & DevOps

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 Technical Documentation

Deliver comprehensive, clear technical specs, metadata lineage documentation, architectural diagrams, and data dictionaries