Lead Data Engineer - Azure Databricks & Lakehouse

EPAM Systems

United States

Remote

USD 140,000 - 170,000

Full time

2 days ago
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Job summary

EPAM Systems is seeking a Senior Data Software Engineer with Azure Databricks expertise to enhance the client's Enterprise Data Lake on Microsoft Azure. You will lead a team of data engineers, design ingestion pipelines, and drive data curation across Bronze-Silver-Gold layers to deliver trusted data for reporting and analytics.

The role focuses on API ingestion from Genesys Cloud, evolving toward near real-time streaming, and collaboration with Solution Architect and stakeholders to enable

Qualifications

  • 3+ years of experience in Big Data/data engineering on Azure Databricks with a track record of leading delivery teams.
  • Experience leading teams and architecture: distributing tasks, code review, finding the right technical solutions and guiding the team to implement them.
  • Knowledge of Medallion Lakehouse architecture, covering both ingestion and curation.
  • Proficiency in Azure Databricks: Workflows/Jobs, Notebooks, Unity Catalog (schemas, views, grants, service principals), SQL Warehouse.
  • Proficiency in Delta Lake: MERGE, SCD Type 2, OPTIMIZE and small-file handling.
  • Understanding of liquid clustering and partitioning: choosing clustering keys, data skipping, and the effect on MERGE performance.
  • Skills in Spark Structured Streaming: Auto Loader, checkpoints, triggers, watermarking, stateful processing, exactly-once delivery into Delta.
  • Proven track record of performance improvements: Spark tuning, Delta file layout, SQL optimization, and compute right-sizing and cost.
  • Proficiency in PySpark, Python and strong SQL.
  • Experience in REST API ingestion: OAuth2, async jobs, pagination, rate and concurrency limits, retries and idempotent reloads.
  • Familiarity with Azure: Data Factory, ADLS Gen2, Key Vault, Azure SQL Database (config-driven frameworks).
  • Background in data modeling, data quality and reconciliation, CI/CD for data platforms (GitHub, PR-based promotion), and ability to create Power BI reports and Databricks dashboards.

Responsibilities

  • Lead the engineering team: break designs into tasks, distribute work, track delivery and remove blockers.
  • Turn designs into working pipelines and find the right technical solutions where a design leaves gaps.
  • Evolve reusable ingestion patterns on the metadata-driven EDL framework.
  • Lead curation across the Medallion layers: append-only Bronze, SCD2 history in Silver, and support for Gold models built with data modelers.
  • Own the physical table design, the Unity Catalog structure and RBAC.
  • Lead data quality and reconciliation: source-to-lake checks, DQ rules, audit logging and alerting.
  • Drive performance improvements: optimize Spark jobs, Delta tables, SQL queries and Power BI models and reduce compute cost.
  • Guide the creation of Power BI reports and Databricks dashboards for business reporting and pipeline monitoring.
  • Review code, enforce engineering standards, and own CI/CD promotion (DEV → TST → PRD).
  • Work with the Solution Architect, platform/CloudOps teams and business stakeholders, and prepare runbooks and handover to operations.

Skills

Azure Databricks
PySpark
Python
SQL
Delta Lake
Spark
Unity Catalog
Data Factory
ADLS Gen2
RBAC
Power BI

Tools

GitHub
Power BI
Delta Lake

Job description

EPAM Systems is seeking a Senior Data Software Engineer with Azure Databricks expertise to enhance the client's Enterprise Data Lake on Microsoft Azure. You will lead a team of data engineers, design ingestion pipelines, and drive data curation across Bronze-Silver-Gold layers to deliver trusted data for reporting and analytics.

The role focuses on API ingestion from Genesys Cloud, evolving toward near real-time streaming, and collaboration with Solution Architect and stakeholders to enable

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