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Senior Software Engineer (Data Engineering)
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingLead design and implementation of analytical solutions on cloud-native and big data stacks
Architect scalable hybrid, on-premise and cloud data solutions
Collaborate with product teams and business stakeholders on architecture and features
Review code and test solutions against engineering best practices
Mentor team members and write project documentation
From the employer’s posting
Lead the design and implementation of innovative analytical solutions using Cloud Native, Big Data and NoSQL technologies
Architect scalable hybrid, on-premise and cloud solutions using best-in-class data frameworks
Collaborate with product teams to evaluate new features, drive architectural decisions and solve complex business problems
Actively participate in code reviews and test solutions to ensure strict adherence to engineering best practices
Foster a high-performance engineering culture by mentoring team members and providing essential tooling and motivation
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
664 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.
- Java
- Python
- Scala
- SQL
- AWS
- Azure
- Databricks
- Docker
- DynamoDB
- Elasticsearch
- Kafka
- Kubernetes
- MongoDB
- NoSQL
- Power BI
- SageMaker
- Spark
- Tableau
- Airflow
- TensorFlow
Where the posting names them
Join EPAM as a Senior Data Software Engineer to design and implement innovative analytical solutions using cloud-native, big data and NoSQL technologies. In this role, you will build robust data ingestion pipelines, model complex data architectures and guide cross-functional teams through critical technical decisions. Your expertise will drive complex architectural decisions, mentor high-performance engineering teams and deliver scalable data platforms that solve critical business challenges. Responsibilities Lead the design and implementation of innovative analytical solutions using Cloud Native, Big Data and NoSQL technologies Architect scalable hybrid, on-premise and cloud solutions using best-in-class data frameworks Collaborate with product teams to evaluate new features, drive architectural decisions and solve complex business problems Build strong strategic partnerships with cross-functional architects and key business stakeholders Actively participate in code reviews and test solutions to ensure strict adherence to engineering best practices Foster a high-performance engineering culture by mentoring team members and providing essential tooling and motivation Write comprehensive project documentation to support long-term system stability and adoption Perform practical performance tuning, infrastructure troubleshooting and continuous optimization of data environments Requirements Extensive programming experience in Python, Java or Scala combined with strong SQL and relational database skills Hands-on expertise with big data frameworks (Spark, Kafka, Airflow) and NoSQL databases (CosmosDB, DynamoDB, Cassandra, MongoDB) Experience designing and administering scalable data platforms across major cloud providers like AWS, Azure, Databricks or AliCloud Deep understanding of distributed computing, data ingestion pipelines (ETL) and modern data warehousing architectures Proficiency in containerization and orchestration using Docker and Kubernetes within CI/CD environments Knowledge of data compliance standards (GDPR, HIPAA) and security best practices for data management High proficiency in business English with exceptional communication skills for direct client engagement Analytical problem-solving skills with the ability to manage multiple priorities and optimize system performance Nice to have Experience with machine learning services such as SageMaker or TensorFlow Familiarity with data visualization tools including Tableau or Power BI Background in enterprise search platforms like Elasticsearch and the ELK stack
Your next step
Complete your application on careers.epam.com. The employer’s form will show what is required.
Already applied? Track this application
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
Join EPAM as a Senior Data Software Engineer to design and implement innovative analytical solutions using cloud-native, big data and NoSQL technologies. In this role, you will build robust data ingestion pipelines, model complex data architectures and guide cross-functional teams through critical technical decisions. Your expertise will drive complex architectural decisions, mentor high-performance engineering teams and deliver scalable data platforms that solve critical business challenges. Responsibilities Lead the design and implementation of innovative analytical solutions using Cloud Native, Big Data and NoSQL technologies Architect scalable hybrid, on-premise and cloud solutions using best-in-class data frameworks Collaborate with product teams to evaluate new features, drive architectural decisions and solve complex business problems Build strong strategic partnerships with cross-functional architects and key business stakeholders Actively participate in code reviews and test solutions to ensure strict adherence to engineering best practices Foster a high-performance engineering culture by mentoring team members and providing essential tooling and motivation Write comprehensive project documentation to support long-term system stability and adoption Perform practical performance tuning, infrastructure troubleshooting and continuous optimization of data environments Requirements Extensive programming experience in Python, Java or Scala combined with strong SQL and relational database skills Hands-on expertise with big data frameworks (Spark, Kafka, Airflow) and NoSQL databases (CosmosDB, DynamoDB, Cassandra, MongoDB) Experience designing and administering scalable data platforms across major cloud providers like AWS, Azure, Databricks or AliCloud Deep understanding of distributed computing, data ingestion pipelines (ETL) and modern data warehousing architectures Proficiency in containerization and orchestration using Docker and Kubernetes within CI/CD environments Knowledge of data compliance standards (GDPR, HIPAA) and security best practices for data management High proficiency in business English with exceptional communication skills for direct client engagement Analytical problem-solving skills with the ability to manage multiple priorities and optimize system performance Nice to have Experience with machine learning services such as SageMaker or TensorFlow Familiarity with data visualization tools including Tableau or Power BI Background in enterprise search platforms like Elasticsearch and the ELK stack
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