Time since we first saw it
Day 0
Early. Similar jobs usually come down between day 5 and day 54.
From 10,704 similar postings that came down. Coming down is not always a hire.
Senior Data Software 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 postingArchitect and build scalable data pipelines that move data reliably across platforms
Build and maintain data ingestion workflows from a range of source systems
Monitor pipeline performance and resolve issues before they cause outages
Diagnose and fix data quality problems across datasets
Review code and write thorough tests to keep quality high
From the employer’s posting
Architect and construct scalable data pipelines that enable dependable data flow across multiple platforms
Build and sustain data ingestion workflows pulling from a range of different source systems
Keep watch over data pipeline performance, stepping in ahead of time to resolve issues and preserve system dependability
Diagnose and fix data quality problems, safeguarding accuracy and consistency across all datasets
Join in on code review sessions to help maintain quality benchmarks
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 4, 2026today
- Recorded sightings
- 1
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.
- SQL
- Databricks
- Delta Lake
- Spark
- SQL Server
- PySpark
Where the posting names them
We're on the lookout for a Senior Data Software Engineer to come aboard our team. This position is a great match for someone who takes pleasure in architecting durable data solutions that power important business choices. You'll collaborate closely with a group that prioritizes clean, thoroughly tested code and disciplined engineering approaches. For anyone energized by tackling large-scale data problems, this role provides ample opportunity for both growth and meaningful contribution Responsibilities Architect and construct scalable data pipelines that enable dependable data flow across multiple platforms Build and sustain data ingestion workflows pulling from a range of different source systems Produce clean, high-performing, thoroughly tested code grounded in solid software engineering principles Partner with teams across different functions to understand data needs and shape them into working technical solutions Keep watch over data pipeline performance, stepping in ahead of time to resolve issues and preserve system dependability Join in on code review sessions to help maintain quality benchmarks and spread knowledge throughout the team Diagnose and fix data quality problems, safeguarding accuracy and consistency across all datasets Help drive continuous enhancement of data architecture practices and engineering standards Create documentation covering technical workflows and solutions to aid knowledge sharing and new team member onboarding Operate within an agile framework, taking part in sprint planning sessions and other recurring team activities Requirements At least 3 years of relevant hands-on professional background Solid practical expertise with PySpark and Spark SQL for constructing and processing large-scale data workflows Background building and overseeing Lakeflow pipelines and Jobs to support data orchestration Skilled in using Auto Loader along with JDBC/CDC ingestion approaches, working with sources like DB2 and SQL Server Strong background with Delta Lake and Unity Catalog for handling data storage and governance needs Experience maintaining data quality standards and performing source reconciliation to ensure dependable, accurate datasets Background writing unit tests through pytest to confirm code correctness and reliability Familiarity with Git and Asset Bundles for managing version control and deployment workflows Upper-intermediate English language skills or higher (B2) Nice to have Background working on DataStage migration initiatives Experience extracting data from Dynamics 365/Dataverse Holding a Databricks certification
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 Software 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're on the lookout for a Senior Data Software Engineer to come aboard our team. This position is a great match for someone who takes pleasure in architecting durable data solutions that power important business choices. You'll collaborate closely with a group that prioritizes clean, thoroughly tested code and disciplined engineering approaches. For anyone energized by tackling large-scale data problems, this role provides ample opportunity for both growth and meaningful contribution Responsibilities Architect and construct scalable data pipelines that enable dependable data flow across multiple platforms Build and sustain data ingestion workflows pulling from a range of different source systems Produce clean, high-performing, thoroughly tested code grounded in solid software engineering principles Partner with teams across different functions to understand data needs and shape them into working technical solutions Keep watch over data pipeline performance, stepping in ahead of time to resolve issues and preserve system dependability Join in on code review sessions to help maintain quality benchmarks and spread knowledge throughout the team Diagnose and fix data quality problems, safeguarding accuracy and consistency across all datasets Help drive continuous enhancement of data architecture practices and engineering standards Create documentation covering technical workflows and solutions to aid knowledge sharing and new team member onboarding Operate within an agile framework, taking part in sprint planning sessions and other recurring team activities Requirements At least 3 years of relevant hands-on professional background Solid practical expertise with PySpark and Spark SQL for constructing and processing large-scale data workflows Background building and overseeing Lakeflow pipelines and Jobs to support data orchestration Skilled in using Auto Loader along with JDBC/CDC ingestion approaches, working with sources like DB2 and SQL Server Strong background with Delta Lake and Unity Catalog for handling data storage and governance needs Experience maintaining data quality standards and performing source reconciliation to ensure dependable, accurate datasets Background writing unit tests through pytest to confirm code correctness and reliability Familiarity with Git and Asset Bundles for managing version control and deployment workflows Upper-intermediate English language skills or higher (B2) Nice to have Background working on DataStage migration initiatives Experience extracting data from Dynamics 365/Dataverse Holding a Databricks certification
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Location not supplied.
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.