8 years
Posted:6 days ago
Job Description: 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
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).
Qualifications: 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.
Free courses, interview questions and practice for each skill.
Full Time
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