EPAM
Architect the future of financial data as a
Lead Data Engineer
at EPAM. You'll design and implement sophisticated data solutions that power critical analytics for Asset Management and Alternative Investments, leveraging AWS and Snowflake to transform complex financial data into actionable business intelligence.
EPAM is where tech talent thrives-building groundbreaking solutions, advancing your skills through world-class learning platforms, and working alongside a global community of problem-solvers to make the future real.
Req# 907289174
RESPONSIBILITIES Architect end-to-end data solutions that transform complex financial information into actionable insights for Asset Management and Alternative Investments Design and optimize high-performance ETL/ELT pipelines using Python, SQL, and AWS technologies to process critical investment data Establish data engineering design patterns and best practices that ensure scalability, reliability, and security across the organization Partner with business stakeholders to translate complex financial requirements into elegant technical solutions Champion robust data governance frameworks that maintain data quality and security throughout the entire data lifecycle Mentor junior engineers and foster a culture of technical excellence and continuous improvement within the data engineering team
REQUIREMENTS
10+ years of data engineering experience with at least 3 years in a leadership role designing enterprise-scale data solutions Expert-level SQL skills with demonstrated ability to optimize complex queries and tune performance in large-scale environments Advanced Python programming expertise applied to data engineering challenges and automation workflows Extensive hands-on experience with AWS data services including S3, Glue, Lambda, Redshift, and Step Functions Production-level Snowflake expertise including data sharing, performance optimization, and cost management Deep understanding of financial data structures and business processes within Asset Management or Alternative Investments Experience implementing CI/CD pipelines and DevOps practices for data engineering workflows Familiarity with orchestration tools like Airflow or dbt (Optional)
Lead Data Engineer
at EPAM. You'll design and implement sophisticated data solutions that power critical analytics for Asset Management and Alternative Investments, leveraging AWS and Snowflake to transform complex financial data into actionable business intelligence.
EPAM is where tech talent thrives-building groundbreaking solutions, advancing your skills through world-class learning platforms, and working alongside a global community of problem-solvers to make the future real.
Req# 907289174
RESPONSIBILITIES Architect end-to-end data solutions that transform complex financial information into actionable insights for Asset Management and Alternative Investments Design and optimize high-performance ETL/ELT pipelines using Python, SQL, and AWS technologies to process critical investment data Establish data engineering design patterns and best practices that ensure scalability, reliability, and security across the organization Partner with business stakeholders to translate complex financial requirements into elegant technical solutions Champion robust data governance frameworks that maintain data quality and security throughout the entire data lifecycle Mentor junior engineers and foster a culture of technical excellence and continuous improvement within the data engineering team
REQUIREMENTS
10+ years of data engineering experience with at least 3 years in a leadership role designing enterprise-scale data solutions Expert-level SQL skills with demonstrated ability to optimize complex queries and tune performance in large-scale environments Advanced Python programming expertise applied to data engineering challenges and automation workflows Extensive hands-on experience with AWS data services including S3, Glue, Lambda, Redshift, and Step Functions Production-level Snowflake expertise including data sharing, performance optimization, and cost management Deep understanding of financial data structures and business processes within Asset Management or Alternative Investments Experience implementing CI/CD pipelines and DevOps practices for data engineering workflows Familiarity with orchestration tools like Airflow or dbt (Optional)