Description :
Job Title : Senior Data Engineer
Location : Indore / Ahmedabad (India)
Experience : 7+ years
Type : Full-time / Contract
Joining : Immediate preferred
About the Role :
We are looking for an experienced Lead Data Engineer to design, build, and maintain scalable data pipelines and ETL workflows using Azure Data Factory (ADF), Databricks, and Power BI / Fabric.
Youll collaborate with analysts, architects, and business stakeholders to deliver end-to-end data solutions that enable data-driven decision-making.
This role requires strong technical expertise, cloud data engineering skills, and the ability to mentor junior team members.
Key Responsibilities :
- Develop and maintain data pipelines using Azure Data Factory (ADF) and Databricks.
- Design and implement Power BI / Fabric dashboards for actionable insights.
- Collaborate with cross-functional teams to understand requirements and deliver solutions.
- Perform ETL operations extract, transform, and load data into Azure Data Lake or Azure SQL.
- Ensure data quality, reliability, and integrity throughout the data lifecycle.
- Automate repetitive data processes for efficient reporting.
- Monitor, troubleshoot, and optimize data pipelines for performance and scalability.
- Write clean, maintainable code for data transformations and automation.
Required Qualifications :
Bachelors degree in Computer Science, IT, or related field.7+ years of experience in Data Engineering, BI Development, or a related field.Hands-on experience with Azure Data Factory (ADF) and Power BI.Strong SQL skills and experience with Azure SQL Database / SQL Server.Proficiency in Python, SQL, or equivalent scripting languages.Knowledge of data warehousing concepts and ETL processes.Experience working with cloud-based data platforms (preferably Microsoft Azure).Strong analytical, troubleshooting, and optimization skills.Preferred Qualifications :
Experience with Azure Databricks or similar data processing frameworks.Knowledge of Microsoft Fabric and data modeling for Power BI.Familiarity with data lake architecture and performance tuning(ref : hirist.tech)