Databricks engineer

7 days ago

Ajmer, India TTC Group Full time

Role : Databricks Engineer Position : Remote Type : Contract Duration : 3 - 6 months (extendable) Role Overview We are seeking a Mid-Level Databricks Engineer with strong data engineering fundamentals and hands-on experience building scalable data pipelines on the Databricks platform. The ideal candidate will be comfortable working with distributed data processing, designing Delta Lake architectures, implementing CI/CD for data workloads, and optimizing Spark jobs for performance and reliability. Required Skills Strong hands-on experience in building data pipeline using scripting language includes Python, Py Spark and SQL Strong working experience with Databricks (Unity Catalog is plus) and Azure Data Factory (ADF) Hands-on working experience with Azure Dev Ops Repo and CI/CD Strong understanding of modern Data Architecture, Data Warehousing concepts, Data Modelling and ETL/ELT processes Understanding of Agile ways of working Any experience working in DBT is a plus Working with Retail Domain is a plus Platform Engineering & Operations Configure and optimize Databricks clusters, including autoscaling, cluster sizing, and runtime selection. Manage databases, schemas, and Delta Lake tables, including vacuuming, Z-ordering, partitioning, and optimization. Work with catalogs, Unity Catalog (UC), and access controls for secure data governance. Monitor and troubleshoot performance issues across jobs, clusters, and workflows. CI/CD & Dev Ops Implement CI/CD pipelines for Databricks workflows using Git Hub Actions / Azure Dev Ops / Git Lab. Work with Databricks Repos and Git workflows (branching, PRs, code reviews). Version and promote data pipelines across environments. Cloud & Integration Integrate Databricks with cloud services such as: Azure: ADLS Gen2, Key Vault, ADF, Event Hub, Synapse AWS: S3, Glue, IAM, Lambda, Kinesis (depending on cloud environment) Work with data ingestion frameworks, messaging systems, and event-driven architectures. Quality, Testing & Documentation Implement unit tests and integration tests using pytest, SQL tests, or dbx testing frameworks. Maintain pipeline documentation, data dictionaries, and technical design artifacts. Ensure high data quality, reliability, and observability.

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