Senior Data Integration Engineer (AI, Python, Airflow)

EPAM Systems; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

EPAM Systems Inc is seeking a Senior Data Integration Engineer with hands-on AI familiarity to 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.

You will design scalable data integration systems, partner with multidisciplinary teams, guide architecture discussions, and mentor junior engineers while delivering high-quality, timely results.

Qualifications

• 3+ years of relevant professional experience.
• Functional knowledge of AI principles for data integration.
• Advanced Python skills for building data integration apps.
• Hands-on with AWS cloud environments.
• Strong data integration background across sources.
• SQL proficiency for relational data handling.
• NoSQL familiarity for unstructured/semi-structured data.
• Understanding of SDLC and CI/CD practices.
• GCP experience for cloud data solutions.
• Airflow, Databricks or Snowflake experience.
• Spark knowledge for large-scale data processing.
• Agile experience and team collaboration.
• English at least Upper-Intermediate (B2).

Responsibilities

• Design and implement scalable data integration systems.
• Collaborate with multidisciplinary teams to meet quality targets.
• Contribute to architecture discussions shaping project direction.
• Perform code reviews and ensure reliable engineering practices.
• Diagnose and fix complex end-to-end pipeline issues.
• Mentor junior engineers and share knowledge.
• Support planning with scope clarification and estimates.
• Track emerging technologies and apply them where valuable.
• Create and maintain documentation of decisions and data flows.
• Coordinate with stakeholders to align objectives and results.

Skills

AI principles familiarity

Cloud data integration experience

Agile methodologies

Mentoring

Time estimation

English communication

Tools

Python

SQL

Airflow

Spark

AWS

GCP

Databricks

Snowflake

NoSQL databases

CI/CD

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.

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