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
Responsibilities
Databricks Platform Engineering
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Design, build, and maintain Databricks workspaces, clusters, and compute pools across dev/test/prod environments.
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Configure and manage Databricks Unity Catalog for data governance, access control, fine-grained permissions, and data lineage.
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Optimize cluster configurations — instance types, auto-scaling policies, spot/preemptible nodes — for cost and performance.
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Implement workspace-level best practices: folder structures, access controls, secret management (Databricks Secrets / Azure Key Vault / AWS Secrets Manager).
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Manage Databricks jobs, workflows, and multi-task job orchestration with dependency management.
Delta Lake & Lakehouse Architecture
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Design and implement Delta Lake tables with appropriate partitioning, Z-ordering, and file compaction (OPTIMIZE / VACUUM).
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Build Medallion Architecture (Bronze / Silver / Gold) layers for structured data lake organization.
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Implement Delta Live Tables (DLT) pipelines for declarative, reliable ETL/ELT with built-in data quality expectations.
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Manage schema evolution, table versioning, time travel, and Change Data Feed (CDF) for incremental processing.
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Design data lakehouse patterns integrating Delta Lake with external systems (Kafka, ADLS, S3, GCS).
Qualifications
Education
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Bachelor's or Master's degree in Computer Science, Information Technology, Data Engineering, or related field.
Experience
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8+ years of total experience in data engineering or software engineering.
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3+ years of dedicated hands-on experience with the Databricks platform in production environments.
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Strong background in big data engineering, cloud data platforms, and distributed computing.
Databricks Platform
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Deep expertise in Databricks Workspaces, Clusters, Jobs, Workflows, and Repos.
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Proficiency with Unity Catalog — metastore setup, catalog/schema/table management, access controls, and data lineage.
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Hands-on experience with Delta Live Tables (DLT) — pipeline development, expectations, and monitoring.
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Strong command of Delta Lake internals — transaction log, ACID guarantees, file layout, and optimization techniques.
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Experience with Databricks SQL Warehouses, SQL Analytics, and dashboard creation.
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Knowledge of Databricks Photon engine, serverless compute, and cost optimization strategies.
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