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Lead Data Integration 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 posting
  • Lead and mentor a team of data integration and ETL engineers

  • Architect end-to-end data pipeline solutions on serverless or hybrid setups

  • Set up orchestration and scheduling with Apache Airflow or cloud-native tools

  • Run code reviews and testing frameworks for SQL, Python and Scala code

  • Present advanced technical architectures to C-level client executives

From the employer’s posting
Guide a team of data integration and ETL engineers, fostering a collaborative, innovation-driven culture
Architect end-to-end data pipeline solutions using serverless frameworks or hybrid setups
Establish robust pipeline scheduling and workflow orchestration using tools like Apache Airflow (Astronomer) or cloud-native schedulers
Conduct regular code reviews and set up testing frameworks to ensure compliant, highly performant, and secure database code (SQL, Python, Scala)
Confidently present advanced technical architectures to C-level client executives
Apply at EPAM Systems

Posting record

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Actively 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 27, 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

Time since we first saw it

Day 2

Early. Similar jobs usually come down between day 5 and day 54.

From 10,703 similar postings that came down. Coming down is not always a hire.

EPAM Systems is hiring

656 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See 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.

  • Bash
  • C
  • Python
  • Scala
  • SQL
  • AWS
  • Azure
  • BigQuery
  • GCP
  • Redshift
  • S3
  • Snowflake
  • Airflow
  • pandas
  • PySpark
Where the posting names them
We are seeking an experienced and visionary Lead Data Integration Engineer to join our growing data solutions team. In this pivotal technical leadership role, you will act as a Tech Lead / Team Lead responsible for architecting, designing, and maintaining complex, enterprise-grade data pipelines. You will lead a high-performing engineering team (5+ engineers), shaping cloud-native and hybrid data solution architectures while establishing best practices. Leveraging your extensive expertise in cloud infrastructure, database modeling, orchestration, and data security, you will transform raw data environments into robust, high-performance, and scalable analytical assets. Responsibilities Guide a team of data integration and ETL engineers, fostering a collaborative, innovation-driven culture. Manage sprint planning, resource allocation, and risk management Conduct regular code reviews and set up testing frameworks to ensure compliant, highly performant, and secure database code (SQL, Python, Scala) Act as a role model, championing modern software development practices (CI/CD, version control via Git, modular code design, automated alerting, and monitoring) Architect end-to-end data pipeline solutions using serverless frameworks or hybrid setups Establish robust pipeline scheduling and workflow orchestration using tools like Apache Airflow (Astronomer) or cloud-native schedulers to achieve high pipeline reliability (>99.5%) and minimize troubleshooting times Design, model, and maintain scalable corporate data systems (OLAP, OLTP, Star/Snowflake schemas, Data Lakes, Lakehouses, and Data Meshes) Implement modern ingestion patterns, CDC methods, micro-batching, delta extracts, and routine partition maintenance Collaborate with product owners, enterprise architects, and business stakeholders to translate complex requirements into detailed technical specifications and data-flow diagrams Confidently present advanced technical architectures to C-level client executives, showcasing ROI, architectural benefits, and performance gains Requirements 5+ years of proven experience in data management, database design, migration, storage, and advanced data modeling Demonstrated experience leading, mentoring, and developing teams of data engineers (experience managing teams of 4–7 engineers is highly preferred) Deep hands-on experience with major ETL tools such as Talend, AWS Glue, Azure Data Factory, GCP Dataflow, or Apache NiFi Strong working experience with orchestration and scheduling engines, particularly Apache Airflow (Astronomer) Strong production coding skills in SQL, Python (PySpark, Pandas), Scala, SparkSQL, or Bash Extensive knowledge of at least one major cloud platform (AWS, Azure, GCP) with emphasis on big data warehousing engines (such as Redshift, Snowflake, Google BigQuery, or Azure Synapse) Proven understanding of cloud security structures (identity and access management, data masking, and RLS) and compliance standards (GDPR, HIPAA, PI) Ability to write high-quality technical design specifications, mapping documentation, and data lineage reports Excellent verbal and written English communication (B2+/C1 level), capable of directly managing international clients and conducting presentations Nice to have Experience architecting fully serverless cloud data pipelines (e.g., combining AWS S3, Athena, and AWS Lambda) Exposure to integrating machine learning models, computer vision, or generative AI workflows into data pipeline ingestion processes Professional certifications in Cloud Architecture (AWS, Azure, GCP), Talend, or Airflow

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 8 other Lead Data Integration Engineer jobs there since November 2026. All 8 are still up.

  1. Place not statedStill up after 3 days, first seen Nov 1
  2. Place not statedStill up after 3 days, first seen Nov 1
  3. Place not statedStill up after 3 days, first seen Nov 1
  4. Place not statedStill up after 3 days, first seen Nov 1
  5. Place not statedStill up after 3 days, first seen Nov 1
  6. Place not statedStill up after 3 days, first seen Nov 1
  7. This jobUp 3 days so far, first seen Nov 1
  8. Place not statedStill up after 0 days, first seen Nov 4
  9. Place not statedStill up after 0 days, first seen Nov 4

Large employers often post one title for several teams, so these can be separate openings.

Job description

View original posting ↗

We are seeking an experienced and visionary Lead Data Integration Engineer to join our growing data solutions team. In this pivotal technical leadership role, you will act as a Tech Lead / Team Lead responsible for architecting, designing, and maintaining complex, enterprise-grade data pipelines. You will lead a high-performing engineering team (5+ engineers), shaping cloud-native and hybrid data solution architectures while establishing best practices. Leveraging your extensive expertise in cloud infrastructure, database modeling, orchestration, and data security, you will transform raw data environments into robust, high-performance, and scalable analytical assets. Responsibilities Guide a team of data integration and ETL engineers, fostering a collaborative, innovation-driven culture. Manage sprint planning, resource allocation, and risk management Conduct regular code reviews and set up testing frameworks to ensure compliant, highly performant, and secure database code (SQL, Python, Scala) Act as a role model, championing modern software development practices (CI/CD, version control via Git, modular code design, automated alerting, and monitoring) Architect end-to-end data pipeline solutions using serverless frameworks or hybrid setups Establish robust pipeline scheduling and workflow orchestration using tools like Apache Airflow (Astronomer) or cloud-native schedulers to achieve high pipeline reliability (>99.5%) and minimize troubleshooting times Design, model, and maintain scalable corporate data systems (OLAP, OLTP, Star/Snowflake schemas, Data Lakes, Lakehouses, and Data Meshes) Implement modern ingestion patterns, CDC methods, micro-batching, delta extracts, and routine partition maintenance Collaborate with product owners, enterprise architects, and business stakeholders to translate complex requirements into detailed technical specifications and data-flow diagrams Confidently present advanced technical architectures to C-level client executives, showcasing ROI, architectural benefits, and performance gains Requirements 5+ years of proven experience in data management, database design, migration, storage, and advanced data modeling Demonstrated experience leading, mentoring, and developing teams of data engineers (experience managing teams of 4–7 engineers is highly preferred) Deep hands-on experience with major ETL tools such as Talend, AWS Glue, Azure Data Factory, GCP Dataflow, or Apache NiFi Strong working experience with orchestration and scheduling engines, particularly Apache Airflow (Astronomer) Strong production coding skills in SQL, Python (PySpark, Pandas), Scala, SparkSQL, or Bash Extensive knowledge of at least one major cloud platform (AWS, Azure, GCP) with emphasis on big data warehousing engines (such as Redshift, Snowflake, Google BigQuery, or Azure Synapse) Proven understanding of cloud security structures (identity and access management, data masking, and RLS) and compliance standards (GDPR, HIPAA, PI) Ability to write high-quality technical design specifications, mapping documentation, and data lineage reports Excellent verbal and written English communication (B2+/C1 level), capable of directly managing international clients and conducting presentations Nice to have Experience architecting fully serverless cloud data pipelines (e.g., combining AWS S3, Athena, and AWS Lambda) Exposure to integrating machine learning models, computer vision, or generative AI workflows into data pipeline ingestion processes Professional certifications in Cloud Architecture (AWS, Azure, GCP), Talend, or Airflow
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