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EXL

Analyzes business data and runs outsourced operations

Databricks Tech Lead

Data EngineeringConfirmed live in the last 24 hours
Full-timeChennai, Tamil Nadu, IndiaNo salary listedIn-person

About the Job

Requirements

  • A Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or a related field.
  • At least 8 years of total experience in data engineering or software engineering.
  • At least 3 years of hands-on production experience with the Databricks platform.
  • A strong background in big data engineering, cloud data platforms, and distributed computing.
  • Deep expertise in Databricks Workspaces, Clusters, Jobs, Workflows, and Repos.
  • Proficiency with Unity Catalog, including metastore setup, catalog/schema/table management, access controls, and data lineage.
  • Hands-on experience with Delta Live Tables (DLT), including pipeline development, expectations, and monitoring.
  • Strong command of Delta Lake internals, including transaction logs, ACID guarantees, file layout, and optimization techniques.
  • Experience with Databricks SQL Warehouses, SQL Analytics, and dashboard creation.
  • Knowledge of the Databricks Photon engine, serverless compute, and cost optimization strategies.

Responsibilities

  • Design, build, and optimize enterprise-scale data lakehouse solutions on the Databricks platform.
  • Create Databricks pipelines delivering financial-crime platforms covering Anti-Money Laundering (AML), Know Your Customer (KYC), Customer Risk Assessment (CRA), sanctions screening, transaction monitoring, fraud detection, and regulatory reporting.
  • Design, build, and maintain Databricks workspaces, clusters, and compute pools across development, test, and production environments.
  • Configure and manage Databricks Unity Catalog for data governance, access control, fine-grained permissions, and data lineage.
  • Optimize cluster configurations, including instance types, auto-scaling policies, and spot/preemptible nodes, for cost and performance.
  • Implement workspace-level best practices for folder structures, access controls, and secret management using Databricks Secrets, Azure Key Vault, or AWS Secrets Manager.
  • Manage Databricks jobs, workflows, and multi-task job orchestration with dependency management.
  • Design and implement Delta Lake tables with appropriate partitioning, Z-ordering, and file compaction using OPTIMIZE and VACUUM.
  • Build Bronze, Silver, and Gold layers using Medallion Architecture for structured data lake organization.
  • Implement Delta Live Tables pipelines for declarative, reliable ETL/ELT with built-in data quality expectations.
  • Manage schema evolution, table versioning, time travel, and Change Data Feed (CDF) for incremental processing.
  • Design data lakehouse patterns integrating Delta Lake with external systems such as Kafka, ADLS, S3, and GCS.

About the Company

EXL

Analyzes business data and runs outsourced operations

EXL analyzes business data and runs outsourced operations for insurers, healthcare payers, banks, retailers, and other large organizations. Its teams combine industry expertise with data engineering and AI to handle tasks such as claims processing, payment reviews, customer service, and finance within existing technology environments. The company also builds software, including LifePRO, which manages insurance policies, and EXLdata.ai, which connects fragmented data for use in AI systems. Clients pay for consulting projects, ongoing managed services, and software delivered through the cloud. EXL was founded in 1999 and is headquartered in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1999

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