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Senior Data Integration Engineer (AI, Python, Airflow)
- 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 cloud-based data integration pipelines
Review and improve existing data pipelines
From the employer’s posting
design, review, and improve cloud-based pipelines
What you’ll bring
All qualificationsCore experience
- Hands-on experience with Python, SQL, Airflow and Spark
- Experience with AWS, GCP, Databricks, or Snowflake
- Hands-on AI familiarity
Qualification wording
using Python, SQL, Airflow, Spark
platforms such as AWS, GCP, Databricks, or Snowflake
hands-on AI familiarity
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
- Oct 30, 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
- Databricks
- GCP
- NoSQL
- Snowflake
- Spark
- Airflow
Where the posting names them
We are delivering complex data integration work and are looking for a Senior Data Integration Engineer with hands-on AI familiarity. You will design, review, and improve cloud-based pipelines using Python, SQL, Airflow, Spark, and platforms such as AWS, GCP, Databricks, or Snowflake in an Agile team. Apply now to build resilient integrations and keep growing your AI skills Responsibilities Design and implement scalable, durable data integration systems that meet business and technical needs Partner with multidisciplinary teams to complete deliverables on schedule and at the expected quality level Shape data integration project direction by actively contributing to architecture discussions Perform code reviews and deliver constructive feedback to maintain dependable engineering practices Analyze and fix complex technical issues across the end-to-end data pipeline lifecycle Support junior engineers’ development through mentoring and knowledge sharing Contribute to planning by clarifying scope and providing accurate time estimates Track emerging technologies and adopt valuable techniques into everyday work Create and maintain clear documentation of key decisions and data workflows for long-term stability Collaborate with stakeholders to define objectives and confirm results match expectations Requirements At least 3 years of applicable, relevant professional experience Functional knowledge of AI principles and tools used to enhance data integration solution development Advanced skill in Python for building and sustaining data integration applications Hands-on background operating within cloud environments built on Amazon Web Services Strong background in Data Integration, joining and consolidating data drawn from multiple sources Skilled in using SQL to organize, manage, and extract data from relational databases Familiarity with NoSQL database systems for handling unstructured and semi-structured data types Understanding of CI/CD practices supporting consistent, automated rollout of software and pipelines Working knowledge of Google Cloud Platform for managing and deploying cloud-centered data solutions Experience with Apache Airflow for scheduling and organizing data-related workflows Practical experience with Databricks or Snowflake for supporting large-scale data processing and analytics Hands-on knowledge of Apache Spark for examining and processing substantial datasets Awareness of SDLC Methodologies and their use in enabling organized, efficient project management Experience working in Agile settings that support iterative, team-oriented development practices Confident English communication skills at a B2 level (Upper-Intermediate) or higher
Your next step
Complete your application on careers.epam.com. The employer’s form will show what is required.
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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
We are delivering complex data integration work and are looking for a Senior Data Integration Engineer with hands-on AI familiarity. You will design, review, and improve cloud-based pipelines using Python, SQL, Airflow, Spark, and platforms such as AWS, GCP, Databricks, or Snowflake in an Agile team. Apply now to build resilient integrations and keep growing your AI skills Responsibilities Design and implement scalable, durable data integration systems that meet business and technical needs Partner with multidisciplinary teams to complete deliverables on schedule and at the expected quality level Shape data integration project direction by actively contributing to architecture discussions Perform code reviews and deliver constructive feedback to maintain dependable engineering practices Analyze and fix complex technical issues across the end-to-end data pipeline lifecycle Support junior engineers’ development through mentoring and knowledge sharing Contribute to planning by clarifying scope and providing accurate time estimates Track emerging technologies and adopt valuable techniques into everyday work Create and maintain clear documentation of key decisions and data workflows for long-term stability Collaborate with stakeholders to define objectives and confirm results match expectations Requirements At least 3 years of applicable, relevant professional experience Functional knowledge of AI principles and tools used to enhance data integration solution development Advanced skill in Python for building and sustaining data integration applications Hands-on background operating within cloud environments built on Amazon Web Services Strong background in Data Integration, joining and consolidating data drawn from multiple sources Skilled in using SQL to organize, manage, and extract data from relational databases Familiarity with NoSQL database systems for handling unstructured and semi-structured data types Understanding of CI/CD practices supporting consistent, automated rollout of software and pipelines Working knowledge of Google Cloud Platform for managing and deploying cloud-centered data solutions Experience with Apache Airflow for scheduling and organizing data-related workflows Practical experience with Databricks or Snowflake for supporting large-scale data processing and analytics Hands-on knowledge of Apache Spark for examining and processing substantial datasets Awareness of SDLC Methodologies and their use in enabling organized, efficient project management Experience working in Agile settings that support iterative, team-oriented development practices Confident English communication skills at a B2 level (Upper-Intermediate) or higher
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