Area(s) of ResponsibilityKey Responsibilities

1. Data Engineering Execution
- Build and maintain ingestion frameworks (ADF / Databricks / Spark)
- Implement Bronze -> Silver transformations aligned to architecture
- Architect data quality checks, schema validation, and contract rules
- Build and optimize robust, high-throughput ELT/ETL pipelines, enabling ingestion, transformation, and curation of structured, semi-structured, and unstructured data.
- Integrate data from multiple on-premise and cloud-based systems, APIs, and third-party sources.
- Implement complex transformations using PySpark, ensuring performance efficiency and code modularity.
- Build orchestration workflows in ADF, including pipelines, triggers, linked services, integration runtimes, and parameterized datasets.
- Familiar with using Databricks Genie.
- Build: Dimensional models (star/snowflake schemas), Fact tables, dimensions, surrogate keys, SCD handling
- Translate Silver datasets into: Analytics-ready models, Consistent KPI definitions, and business logic




- Ensure: Consistency across domains (common dimensions, conformed models), Reusability and scalability of models

- Databricks & PySpark Engineering

- Develop scalable transformation scripts using PySpark on Databricks, applying advanced optimizations like caching, partitioning, and Delta Lake capabilities.
- Implement Delta Lake features-ACID transactions, schema enforcement, schema evolution, and time travel-across the data lifecycle.
- Perform performance tuning, handling bottlenecks related to cluster configuration, shuffle operations, joins, and parallelization.
- Collaborate with platform teams to manage Databricks clusters, jobs, notebooks, and CI/CD integrations.

Locations

- Country/Region: IN
- Requisition ID: 38967
- Work Model:
- Position Type:
- Salary Range:
- Location: INDIA - PUNE - BIRLASOFT OFFICE - HINJAWADI

📌 Title: Azure Databricks Developer (India)
🏢 Birlasoft
📍 India