Senior Databricks Engineer

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EXL

WebsiteLinkedInAll Job Openings

10,000+ employees

💰 $2M Venture Round on 2015-01

Choosing a digital partner is about more than capabilities — it’s about collaboration and character.

📋 Description

• Ingestion & Transformation: Design and optimize high-volume ETL/ELT pipelines using Delta Live Tables (DLT) and PySpark, ensuring data integrity across the Bronze, Silver, and Gold layers. • Workflow Orchestration: Develop and maintain sophisticated pipelines using Databricks Workflows or Airflow, focusing on modularity, reusability, and automated error handling. • Streaming & Real-time Integration: Implement real-time data flows utilizing Structured Streaming and Kafka/Event Hubs to enable immediate data availability for downstream consumption. • Data Security & Privacy: Enforce data anonymization and fine-grained access controls to ensure compliance with global regulations (GDPR/CCPA/HIPAA). • DataOps & DevOps: Implement CI/CD patterns using Databricks Asset Bundles (DABs), Terraform, and Git to automate environment parity and deployments. • Open Table Formats: Manage and optimize Delta Lake storage, utilizing advanced features like Liquid Clustering, Z-Ordering, and Change Data Feed (CDF). • Compute Engine Optimization: Drive cost efficiency and performance by optimizing Spark configurations, Photon engine utilization, and Serverless SQL Warehouses. • Observability & Monitoring: Integrate comprehensive monitoring and alerting (e.g., Databricks System Tables, Grafana, or Splunk) to rapidly identify bottlenecks and troubleshoot production issues.

🎯 Requirements

• 6+ Years of hands-on, progressive experience in Data Engineering, with at least 5 years focused heavily on the Databricks platform. • Architectural Understanding: Expert knowledge of Medallion Architecture, Data Vault 2.0 or Dimensional Modeling, and modern Lakehouse design patterns. • Scale Expertise: Proven track record of building and managing large-scale data infrastructure (Petabyte-scale) in cloud-native environments. • Industry Experience: Experience in the Insurance or Financial Services industry is preferred (focusing on claims, policy, or risk data). • Technical Toolset: • Cloud Environment: Azure (preferred), AWS. • Databricks Stack: Unity Catalog, Delta Live Tables, Databricks SQL, MLflow. • Core Languages: Expert-level SQL, Python, and PySpark. • Supporting Tools: dbt (Databricks adapter), Git, and Orchestration tools.

🏖️ Benefits

• Work From Home