Lead Data Engineer (Databricks & Spark)

EPAM Systems, Inc.; United States; Remote; USD 150,000 - 190,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

LinkedIn Learning access

Global career opportunities

Volunteer opportunities

Employee groups

Job summary

EPAM Systems, Inc. is seeking a Lead Data Engineer to shape scalable ingestion, transformation, and governed data products on Databricks. You will couple hands-on delivery with technical leadership and architecture to enable self-service analytics and AI-assisted engineering.

Responsibilities include designing ingestion and transformation frameworks on Databricks, building batch and streaming pipelines, and mentoring engineers across teams to elevate data platforms and semantic models.

Qualifications

• 5+ years of data engineering experience with production-grade platforms.
• Advanced Apache Spark and PySpark expertise for scalable pipeline development.
• Strong SQL skills for transformation, modeling, and performance tuning.

Responsibilities

• Design scalable ingestion and transformation frameworks on Databricks.
• Lead end-to-end data products from ingestion through governed consumption layers.
• Define and enforce Databricks best practices for medallion architecture.
• Mentor engineers and drive reusable data engineering frameworks.

Skills

Databricks

Spark

PySpark

SQL

Data ingestion

Data transformation

Data modeling

Data quality

Leadership

Mentoring

Tools

Scala

Job description

We are building a next-generation analytics platform and need a Lead Data Engineer to shape scalable ingestion, transformation, and governed data products on Databricks. You will combine hands-on delivery with technical leadership and architecture to enable self-service analytics and AI-assisted engineering.ResponsibilitiesDesign scalable data ingestion and transformation frameworks on DatabricksDefine and enforce Databricks best practices for medallion layers and operational excellenceBuild batch and streaming pipelines using Apache Spark and PySparkDeliver end-to-end data products from ingestion through governed consumption layersDevelop trusted analytical datasets and semantic models for reporting and self-service analyticsImplement data quality, lineage, monitoring, and observability standardsLead proof-of-concepts and evaluate emerging capabilities in the Databricks ecosystemMentor engineers and drive reusable frameworks adopted across teamsRequirements5+ years of data engineering experience with production-grade platformsStrong Databricks experience in enterprise production environmentsLead-level technical leadership skills to drive standards and mentor engineersEnd-to-end delivery experience across ingestion, transformation, semantic layers, and reportingAdvanced Apache Spark and PySpark expertise for scalable pipeline developmentAdvanced SQL skills for transformation, modeling, and performance tuningUpper-Intermediate English proficiency (B2) for leading technical discussionsNice to haveData architecture experience for enterprise lakehouse patternsData solution architecture skills to define scalable platform designsScala proficiency for Spark development and optimizationWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedIn