Location Name: Pune Corporate Office - Mantri

Job Purpose

Responsible for analyzing, transforming, and deriving insights from large-scale data using Databricks and contemporary data stack technologies. Designs and executes data pipelines using SQL and PySpark on Databricks, leveraging Unity Catalog for data governance and management. Collaborates with cross-functional teams to build data models, perform exploratory analysis, and deliver actionable insights. Optimizes queries on SQL Warehouses, integrates external APIs where needed, and ensures data quality and reliability across workflows

Duties And Responsibilities

Develop, maintain, and optimize scalable data pipelines using Databricks (PySpark and SQL).
Perform data extraction, transformation, and loading (ETL/ELT) for large and complex datasets.
Analyse data to generate actionable insights supporting business decision-making.
Design and manage data models and curated datasets within Unity Catalog.
Ensure data quality, consistency, and reliability through validation and monitoring frameworks.




Optimize query performance on SQL Warehouses for faster analytics and reporting.
Collaborate with business stakeholders to understand requirements and translate them into data solutions.

Key Decisions / Dimensions

Selection of appropriate data models, pipeline design, and transformation logic to meet business requirements efficiently.
Optimization strategies for query performance, compute usage, and cost on Databricks SQL Warehouses and Spark workloads.
Choice of data sources, integration approaches, and data quality rules to ensure reliable and governed datasets

Major Challenges

Handling large-scale, distributed datasets in Databricks while maintaining performance and cost efficiency of pipelines and queries.
Ensuring data quality and consistency across multiple sources, evolving schemas, and governed settings like Unity Catalog.
Translating ambiguous business requirements into scalable data models and actionable insi

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