Data Engineer

Greeting from IndusInd Bank!! We are currently hiring for Senior Data Engineer -Azure, Databricks & Snowflake Location- Gurgaon Role Details: We are looking for a highly hands-on Data Engineer with deep expertise in Azure Data Platform, Databricks, and Snowflake to design and build scalable data solutions. The ideal candidate should have a strong foundation in Medallion (Bronze–Silver–Gold) architecture and expert in designing analytics-ready data models using Star Schema.

The role requires active involvement in data pipeline development, modelling, and performance optimization across cloud platforms. Overall, Job Description Data Architecture & Modeling Strong understanding and implementation of: Medallion Architecture (Bronze, Silver, Gold layers) Data Lakehouse concepts Expertise in: Designing Star Schema / Dimensional Models Fact and dimension table design Data modeling for analytics and BI consumption Snowflake (Preferred) Hands-on experience in: Snowflake data warehouse (schema design, performance tuning) Data loading and transformations Query optimization and cost considerations Programming & Querying Strong coding skills in: PySpark (mandatory) Python SQL (advanced level – joins, window functions, optimization) Ability to: Write efficient and scalable transformation logic Integration & Platform Capabilities Experience with: API-based data ingestion Self-Hosted Integration Runtime (SHIR) Understanding of: Data ingestion patterns (batch, streaming – good to have) CI/CD pipelines (Azure DevOps) Good to Have Power BI / Tableau integration Knowledge of: Azure Synapse SSIS migration to ADF Data governance and catalog tools Key Responsibilities Hands-on Data Engineering Design and build scalable data pipelines using Azure and Databricks Develop and maintain Databricks notebooks and jobs using PySpark Implement data transformations across Medallion layers Data Modeling & Architecture Design and implement: Star Schema data models for analytics Optimized fact and dimension tables Ensure: Data is structured for BI and reporting consumption Platform Development Build pipelines between: On-prem / external sources → ADLS / Blob ADLS / Blob → Databricks / Snowflake / Synapse Work on: Data ingestion, transformation, and serving layers Performance & Optimization Optimize: Databricks jobs and Spark performance SQL queries and Snowflake workloads Ensure: Efficient data processing and reduced latency Collaboration Work closely with: Data Analysts (to enable reporting use cases) Architects and platform teams Translate business requirements into technical data solutions Maintenance & Troubleshooting Monitor pipelines and resolve failures Debug data quality issues and pipeline errors Maintain proper documentation of pipelines and data model/ EDUCATION -Essential requirements: Bachelor’s degree in Computer Science or equivalent Preferred certifications: Azure Data Engineer (DP-203) Azure Fundamentals (AZ-900) Preferred: Technical Skills Core Data Engineering (Must-Have) Strong hands-on expertise in: Azure Databricks (PySpark, Delta Lake, Notebooks, Jobs) Azure Data Factory (ADF) – pipelines, triggers, orchestration ADLS Gen2 / Azure Blob Storage Experience building: End-to-end data pipelines (batch & near real-time) Databricks certification (good to have) WORK EXPERIENCE 5–8 years of overall experience in Data Engineering Minimum 3–5 years of hands-on experience in: Azure Data Platform (ADF, ADLS, Synapse) Azure Databricks (must-have) Snowflake (preferred / strong advantage) Proven experience working on large-scale data platforms and distributed data systems Desired Behavioral / Functional Traits Strong hands-on mindset with high ownership Excellent problem-solving and analytical skills Ability to work in a fast-paced, delivery-oriented environment Good communication and collaboration skills Attention to data quality, scalability, and performance If you are interested in this opportunity, please share your updated resume at . Along with your resume, kindly mention: - Current CTC - Expected CTC - Notice Period Regards, Team HR