Databricks Tech Lead

We are looking for a skilled and passionate Databricks Engineer to design, build, and optimize enterprise-scale data lakehouse solutions on the Databricks platform. The successful candidate will be responsible for creating Databricks pipeline 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

Databricks Platform Engineering

-

Design, build, and maintain Databricks workspaces, clusters, and compute pools across dev/test/prod environments.

-

Configure and manage Databricks Unity Catalog for data governance, access control, fine-grained permissions, and data lineage.

-

Optimize cluster configurations — instance types, auto-scaling policies, spot/preemptible nodes — for cost and performance.

-

Implement workspace-level best practices: folder structures, access controls, secret management (Databricks Secrets / Azure Key Vault / AWS Secrets Manager).

-

Manage Databricks jobs, workflows, and multi-task job orchestration with dependency management.

Delta Lake & Lakehouse Architecture

-

Design and implement Delta Lake tables with appropriate partitioning, Z-ordering, and file compaction (OPTIMIZE / VACUUM).

-

Build Medallion Architecture (Bronze / Silver / Gold) layers for structured data lake organization.

-

Implement Delta Live Tables (DLT) 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 (Kafka, ADLS, S3, GCS).

Education

-

Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field.

Experience

-

8+ years of total experience in data engineering or software engineering.

-

3+ years of dedicated hands-on experience with the Databricks platform in production environments.

-

Strong background in big data engineering, cloud data platforms, and distributed computing.

Databricks Platform

-

Deep expertise in Databricks Workspaces, Clusters, Jobs, Workflows, and Repos.

-

Proficiency with Unity Catalog — metastore setup, catalog/schema/table management, access controls, and data lineage.

-

Hands-on experience with Delta Live Tables (DLT) — pipeline development, expectations, and monitoring.

-

Strong command of Delta Lake internals — transaction log, ACID guarantees, file layout, and optimization techniques.

-

Experience with Databricks SQL Warehouses, SQL Analytics, and dashboard creation.

-

Knowledge of Databricks Photon engine, serverless compute, and cost optimization strategies.