– Data Engineer

Employment Type: Full-Time Employment (FTE)

Work Mode: Onsite

Locations: Hyderabad & Indore

Notice Period: Immediate to 30 Days

Interview Process

First Round: Virtual Interview

Final Round: Face-to-Face (F2F)

Job Summary

We are looking for skilled and experienced Data Engineers with strong expertise in Databricks, Microsoft Fabric, or Snowflake, along with Power BI. The ideal candidates should have hands-on experience in designing, developing, and optimizing scalable data pipelines, data integration solutions, and analytics platforms.

Key Responsibilities

Design, develop, and maintain ETL/ELT data pipelines using Databricks, Microsoft Fabric, Azure Data Factory (ADF), or Snowflake.

Build and optimize data workflows for performance, scalability, and cost efficiency.

Develop data processing and transformation solutions using Python, PySpark, and SQL.

Implement Medallion Architecture (Bronze, Silver, and Gold layers) and scalable data models.

Design and manage data lakes, data warehouses, and lakehouse architectures.

Integrate data engineering solutions with Power BI and downstream analytics applications.

Develop and maintain Power BI dashboards, reports, and data models.

Work on data migration projects from legacy platforms to contemporary data platforms.

Ensure data quality, integrity, governance, and security across platforms.

Automate workflows and support CI/CD deployments using Git and DevOps practices.

Monitor, troubleshoot, and optimize data pipelines and dashboards.

Collaborate with cross-functional teams to understand business requirements and deliver effective data solutions.

Required Skills & Experience

3–10+ years of overall experience in Data Engineering.

Hands-on experience with at least one of the following: Databricks, Microsoft Fabric, Azure Data Factory (ADF), or Snowflake.





Strong programming skills in Python.

Strong hands-on experience with PySpark / Apache Spark for large-scale data processing.

Strong SQL skills, including complex queries and data transformations.

Experience designing and developing scalable ETL/ELT pipelines.

Hands-on experience with Power BI, including data modeling, DAX, dashboard development, and performance optimization.

Experience with Dataflow Gen2 for data ingestion and transformation within Microsoft Fabric.

Good understanding of Star Schema, dimensional modeling, and Medallion Architecture.

Experience working with at least one cloud platform: Azure, AWS, or GCP.

Knowledge of data lakes, data warehouses, and lakehouse architectures.

Experience with data migration projects such as Informatica to Fabric, SSIS to ADF, or legacy platforms to Databricks/Fabric.

Experience with Git, CI/CD pipelines, and DevOps practices.

Understanding of data governance, lineage, security, and compliance.

Platform & Technical Skills

Databricks / Microsoft Fabric / Azure Data Factory.

Snowflake / Azure Synapse.

Python / PySpark / SQL.

Power BI / DAX / Dataflow Gen2.

Delta Lake and modern cloud data architectures.

Azure / AWS / GCP.

ETL/ELT and data pipeline development.

Data modeling and Medallion Architecture.

Preferred / Good to Have

Experience with streaming technologies such as Kafka, Azure Event Hubs, or Kinesis.

Knowledge of Delta Lake, Snowflake, and Synapse performance optimization.

Experience with Databricks platform optimization and its broader ecosystem.

Exposure to AI/ML pipelines, MLOps, and GenAI data workloads.

Understanding of Infrastructure as Code and advanced DevOps practices.

Experience delivering multiple data engineering projects; 6–8 Databricks projects preferred for Databricks-focused roles.

Databricks Professional Certification is preferred but not mandatory.

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