Lead Data Engineer

EPAM Systems, Inc.; United States; Remote; USD 140,000 - 200,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off and sick leave

Upskilling, reskilling and certif...

Job summary

EPAM Systems, Inc. is seeking a Lead Data Engineer to build a next-generation analytics platform with a strong focus on Databricks and scalable data products.

You will blend hands-on delivery with technical leadership across ingestion, modeling, governance, and AI-enabled engineering practices. You will design scalable data frameworks, implement batch and streaming pipelines, and deliver trusted datasets and governed layers for reporting.

Qualifications

• 5+ years of data engineering experience.
• 1+ years of technical leadership guiding engineering standards.
• Experience delivering end-to-end analytics solutions.
• Advanced Spark and PySpark expertise.
• Databricks production experience and optimization.
• Strong SQL for data transformation and analytics.
• Knowledge of data governance, security, and lineage.
• CI/CD and Data Engineering SDLC practices.
• English proficiency at least B2 for collaboration.

Responsibilities

• Design scalable data ingestion, transformation, and data product frameworks.
• Build batch, near real-time, and streaming pipelines on Databricks.
• Deliver end-to-end data products for analytics across domains.
• Develop trusted datasets, semantic models, and governed layers.
• Implement data quality, lineage, monitoring, and observability.
• Enable self-service analytics with reusable datasets and features.
• Lead POCs and evaluate new Databricks capabilities.
• Define AI SDLC patterns and mentor engineers.

Skills

Data engineering experience

Technical leadership

Communication

English (B2)

Education

Bachelor's degree in CS or related

Tools

Databricks

Apache Spark

PySpark

SQL

CI/CD

Data governance

Job description

We are looking for a Lead Data Engineer to build and evolve a next-generation analytics platform with a strong focus on Databricks and scalable data products. You will combine hands-on delivery with technical leadership across ingestion, modeling, governance, and AI-enabled engineering practices.ResponsibilitiesDesign scalable data ingestion, transformation, and data product frameworksDefine Databricks best practices, including Medallion Architecture, optimization, governance, and operational standardsBuild batch, near real-time, and streaming pipelines using Databricks capabilitiesDeliver end-to-end data products that support analytics use cases across domainsDevelop trusted analytical datasets, semantic models, and governed consumption layers for reportingImplement data quality, lineage, monitoring, and observability practices across pipelinesEnable self-service analytics through reusable, business-ready datasets and platform featuresLead proof-of-concepts and evaluate emerging capabilities across the Databricks ecosystemDefine AI SDLC practices and AI-assisted development patterns to accelerate deliveryPartner with engineering, analytics, product, and business stakeholders and mentor engineers on best practicesRequirements5+ years of data engineering experience1+ years of technical leadership experience guiding engineering standards and best practicesStrong platform delivery experience building enterprise analytics solutions end to endAdvanced Apache Spark and PySpark expertise for large-scale processingStrong Databricks production experience with performance optimization and operational excellenceAdvanced SQL skills for transformation, modeling, and analytics consumptionStrong data governance knowledge including security, quality, and lineage practicesSolid CI/CD experience and Data Engineering SDLC best practicesStrong communication skills to lead technical discussions with cross-functional stakeholdersUpper-Intermediate English proficiency (B2) for day-to-day collaborationNice to haveData Architecture experience designing lakehouse patterns and enterprise data platformsData Solution Architecture experience translating analytics needs into scalable designsScala proficiency for Spark-based 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