IN-Senior Associate_ Databricks Senior Data Engineer_Data and Analytics_Advisory_Bangalore

Job Description & Summary:  

We are seeking hands-on Databricks Data Engineer with 5–7 years of experience who can design, build, and optimize scalable data pipelines on the Databricks Lakehouse. The ideal candidate is strong in SQL, Python, and PySpark, understands Delta Lake inside out, and is experienced with production-grade ETL/ELT, orchestration, cost/performance optimization, and data governance (e.g., Unity Catalog). 

Candidate should have hands-on knowledge of Azure ADF and ADLS. 

Responsibilities: 

You will work on: 

• Build reliable, scalable batch and streaming pipelines using PySpark and Databricks Workflows/Jobs. 

• Implement Delta Lake best practices: schema enforcement/evolution, ACID transactions, time travel, OPTIMIZE/ZORDER, and VACUUM. 

• Develop Delta Live Tables (DLT) or Structured Streaming pipelines with Auto Loader for ingestion. 

• Write robust modular code in Python (packaging, logging, configuration, error handling). 

• Write efficient and scalable SQL queries for data extraction and reporting. 

• Optimize Spark jobs (partitions, joins, bucketing, caching, AQE, broadcast hints, file sizing). 

• Familiarity with SQL Warehouses, Photon, DBR versions, cluster policies, and pools. 

• Workflows/Jobs orchestration: tasks, dependencies, parameters, retries, alerts, schedules. 

• Unity Catalog: permissions, data lineage, audit, external locations, shares; catalog-first design. 

• Ensure idempotent, repayable, and incremental pipelines with proper checkpoints and watermarks. 

• Implement data quality checks (expectations tests in DLT/Great Expectations), unit/integration tests for pipelines. 

• Ensure data quality, integrity, and governance across the pipeline. 

• Work with CI/CD tools to automate deployment and testing of data workflows. 

• Work with stakeholders to define data SLAs, schemas, and interface contracts. 

• Document pipelines, data sets (data dictionary, lineage), and usage guidelines. 

 
 
Primary Skills: 

• Databricks Platform 

• PySpark 

• SQL 

• Data Modelling 

• Python (Scripting, Data Manipulation) 

• Azure – ADF, ADLS 

Secondary Skills: 

• CI/CD (Git, Jenkins, Azure DevOps, etc.) 

Mandatory skill sets: 

Databricks certified Data Engineer Associate 

Preferred skill sets: 

Analytical mindset with strong problem-solving ability 

Years of experience required: 

Experience: 5 – 7 Years 

Education Qualification: