Senior Data Integration Engineer (AI, Python, Databricks)

EPAM Systems; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

EPAM Systems Inc. is seeking a Senior Data Integration Engineer in the United States to design and run cloud-based data pipelines using Python, SQL, Airflow, Spark, and platforms like Databricks or Snowflake.

You will partner with a collaborative team to deliver scalable, reliable data integration solutions. The role requires practical AI familiarity, strong cloud experience (AWS and GCP), and hands-on knowledge of Databricks/Snowflake and Spark.

Qualifications

• 3+ years of relevant professional experience.
• Knowledge of AI principles applied to data integration.
• Advanced Python for data integration applications.
• Hands-on AWS cloud experience.
• Strong SQL skills for relational databases.
• Familiarity with NoSQL databases and unstructured data.
• Understanding of CI/CD practices.
• Experience with Google Cloud Platform.
• Experience with Apache Airflow.
• Experience with Databricks or Snowflake.
• Hands-on Apache Spark.
• Experience in Agile environments.
• Proficient English communication at B2 level or higher.

Responsibilities

• Design scalable, long-lasting data integration systems that satisfy business and technical needs.
• Collaborate with cross-functional teams to deliver work on time while meeting quality standards.
• Contribute to architecture discussions by sharing input that shapes data integration direction.
• Review peers' code and provide actionable feedback to uphold reliable engineering practices.
• Troubleshoot complex technical problems that arise across the data pipeline lifecycle.
• Mentor junior colleagues by sharing knowledge that strengthens their technical skills.
• Support planning activities by clarifying scope and providing trustworthy time estimates.
• Stay current with evolving technologies and introduce valuable approaches into day-to-day work.
• Maintain clear documentation of key technical decisions and data workflows to ensure long-term stability.
• Partner with stakeholders to define goals and verify outcomes meet expectations.

Skills

Python proficiency

SQL proficiency

CI/CD understanding

Agile experience

English communication

Tools

Airflow

Databricks

Snowflake

Apache Spark

Google Cloud Platform

Amazon Web Services

Job description

We are building dependable, scalable data integration platforms and want a Senior Data Integration Engineer who brings practical AI familiarity. You will partner with a collaborative team to design and run cloud-based pipelines using Python, SQL, Airflow, Spark, and tools like Databricks or Snowflake.

Responsibilities

• Design scalable, long-lasting data integration systems that satisfy both business and technical needs.
• Collaborate with cross-functional teams to deliver work on time while meeting quality standards.
• Contribute to architecture discussions by sharing input that shapes data integration direction.
• Review peers' code and provide actionable feedback to uphold reliable engineering practices.
• Troubleshoot complex technical problems that arise across the data pipeline lifecycle.
• Mentor junior colleagues by sharing knowledge that strengthens their technical skills.
• Support planning activities by clarifying scope and providing trustworthy time estimates.
• Stay current with evolving technologies and introduce valuable approaches into day-to-day work.
• Maintain clear documentation of key technical decisions and data workflows to ensure long-term stability.
• Partner with stakeholders to define goals and verify outcomes meet expectations.

Requirements

• At least 3 years of applicable, relevant professional experience.
• Functional knowledge of AI principles and tools, applied to improve data integration solution development.
• Advanced proficiency in Python for developing and maintaining data integration applications.
• Hands-on background working in cloud environments built on Amazon Web Services.
• Strong foundation in Data Integration, combining and harmonizing data from multiple sources.
• Solid SQL skills for structuring, managing, and querying relational databases.
• Familiarity with NoSQL database systems to work with unstructured and semi-structured data.
• Understanding of CI/CD practices that enable consistent, automated deployment of software and pipelines.
• Working knowledge of Google Cloud Platform for operating and deploying cloud-centered data solutions.
• Experience with Apache Airflow to schedule, orchestrate, and monitor data workflows.
• Practical experience with Databricks or Snowflake to support large-scale processing and analytics.
• Hands-on knowledge of Apache Spark for processing and analyzing substantial datasets.
• Awareness of SDLC Methodologies and how they support organized, efficient project delivery.
• Experience working in Agile settings that encourage iterative, team-oriented development.
• Confident English communication skills at a B2 level (Upper-Intermediate) or higher.