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Day 2
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Senior Data Engineer
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Work setup in the employer’s posting: TELECOMMUTE
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingDesign, develop and maintain scalable data pipelines and processing solutions
Build and optimize ETL/ELT processes for structured and unstructured data
Integrate data from internal and external sources and ensure quality
Monitor, troubleshoot and optimize pipelines and related infrastructure
Provide technical guidance and mentorship to less experienced team members
From the employer’s posting
Design, develop, and maintain scalable and reliable data pipelines and data processing solutions
Build and optimize ETL/ELT processes for structured and unstructured data
Integrate data from various internal and external sources and ensure data consistency and quality
Monitor, troubleshoot, and optimize data pipelines and related infrastructure
Provide technical guidance and mentorship to less experienced team members
Posting record
Report an errorActively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 1, 20262 days ago
- Recorded sightings
- 4
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Sep 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
EPAM Systems is hiring
656 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- SQL
- AWS
- Azure
- Databricks
- dbt
- GCP
- Kafka
- Looker
- Power BI
- Spark
- Tableau
- Airflow
Where the posting names them
We are currently seeking a Senior Data Engineer to join our dynamic team. In this role, you will be responsible for designing, developing, and maintaining reliable and scalable data solutions across the data ecosystem. You will work with diverse data sources, modern cloud technologies, and analytical platforms, collaborating closely with engineering, analytics, and business teams to turn complex data into valuable insights and products. Responsibilities Design, develop, and maintain scalable and reliable data pipelines and data processing solutions Build and optimize ETL/ELT processes for structured and unstructured data Work with relational and cloud-based data warehouses and storage solutions Develop efficient SQL queries and optimize data models, pipelines, and data processing workflows Integrate data from various internal and external sources and ensure data consistency and quality Contribute to the design and evolution of data architectures and engineering best practices Monitor, troubleshoot, and optimize data pipelines and related infrastructure Collaborate with Data Analysts, Data Scientists, Software Engineers, and other stakeholders to deliver data-driven solutions Participate in technical discussions, architecture decisions, code reviews, and continuous improvement initiatives Ensure data solutions are scalable, maintainable, secure, and reliable Provide technical guidance and mentorship to less experienced team members Requirements 5+ years of professional experience in Data Engineering, Software Engineering, or a related technical field Strong proficiency in SQL and solid understanding of relational databases and data modeling Hands-on experience with building and maintaining data pipelines and ETL/ELT processes Experience with at least one cloud platform, such as AWS, GCP, or Azure Experience with modern data warehouses, data lakes, or cloud storage solutions Good understanding of data engineering concepts, distributed data processing, and data architecture Experience with Python or another programming language commonly used for data engineering Strong problem-solving and analytical skills, with the ability to work with complex data-related challenges Ability to work effectively in a cross-functional and international team Good understanding of software engineering practices, including version control, testing, code review, and CI/CD Fluency in English at an Upper-Intermediate level Nice to have Experience with Apache Spark, Databricks, Airflow, dbt, Kafka, or similar data technologies Experience with AWS, GCP, or Azure data services Knowledge of BI and data visualization tools such as Power BI, Tableau, Looker, or similar Experience with MicroStrategy or other enterprise BI platforms Experience with infrastructure-as-code and containerization technologies Understanding of data governance, data quality, security, and observability practices Experience working with large-scale or real-time data processing
Your next step
Complete your application on careers.epam.com. The employer’s form will show what is required.
Already applied? Track this application
Has EPAM Systems posted this job before?
Yes. We’ve followed 24 other Senior Data Engineer jobs there since November 2026. All 24 are still up.
Large employers often post one title for several teams, so these can be separate openings.
Job description
We are currently seeking a Senior Data Engineer to join our dynamic team. In this role, you will be responsible for designing, developing, and maintaining reliable and scalable data solutions across the data ecosystem. You will work with diverse data sources, modern cloud technologies, and analytical platforms, collaborating closely with engineering, analytics, and business teams to turn complex data into valuable insights and products. Responsibilities Design, develop, and maintain scalable and reliable data pipelines and data processing solutions Build and optimize ETL/ELT processes for structured and unstructured data Work with relational and cloud-based data warehouses and storage solutions Develop efficient SQL queries and optimize data models, pipelines, and data processing workflows Integrate data from various internal and external sources and ensure data consistency and quality Contribute to the design and evolution of data architectures and engineering best practices Monitor, troubleshoot, and optimize data pipelines and related infrastructure Collaborate with Data Analysts, Data Scientists, Software Engineers, and other stakeholders to deliver data-driven solutions Participate in technical discussions, architecture decisions, code reviews, and continuous improvement initiatives Ensure data solutions are scalable, maintainable, secure, and reliable Provide technical guidance and mentorship to less experienced team members Requirements 5+ years of professional experience in Data Engineering, Software Engineering, or a related technical field Strong proficiency in SQL and solid understanding of relational databases and data modeling Hands-on experience with building and maintaining data pipelines and ETL/ELT processes Experience with at least one cloud platform, such as AWS, GCP, or Azure Experience with modern data warehouses, data lakes, or cloud storage solutions Good understanding of data engineering concepts, distributed data processing, and data architecture Experience with Python or another programming language commonly used for data engineering Strong problem-solving and analytical skills, with the ability to work with complex data-related challenges Ability to work effectively in a cross-functional and international team Good understanding of software engineering practices, including version control, testing, code review, and CI/CD Fluency in English at an Upper-Intermediate level Nice to have Experience with Apache Spark, Databricks, Airflow, dbt, Kafka, or similar data technologies Experience with AWS, GCP, or Azure data services Knowledge of BI and data visualization tools such as Power BI, Tableau, Looker, or similar Experience with MicroStrategy or other enterprise BI platforms Experience with infrastructure-as-code and containerization technologies Understanding of data governance, data quality, security, and observability practices Experience working with large-scale or real-time data processing
Source details
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