Lead I - Data Engineering

Job Title: Senior Data Engineer Location Pune, India (Hybrid) Experience 6–10 Years Job Summary We are looking for a skilled and experienced Senior Data Engineer to join our data engineering team. The ideal candidate will have strong expertise in SQL, Data Analytics, Azure Data Factory (ADF), NoSQL databases (MongoDB), and Data Lake technologies, with hands-on experience in designing, developing, and maintaining scalable data pipelines and data integration solutions on Azure.

The role requires close collaboration with business analysts, data analysts, and engineering teams to deliver reliable and high-quality data solutions that support analytics and reporting initiatives.

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines using Azure Data Factory. Develop complex SQL queries, stored procedures, views, and performance optimization strategies for large datasets. Build and maintain data integration workflows across multiple source systems, including relational and NoSQL databases. Design and manage data ingestion, transformation, and storage processes in Azure Data Lake.

Support data analytics and reporting initiatives by ensuring data availability, accuracy, and consistency. Collaborate with data analysts and business stakeholders to understand data requirements and translate them into technical solutions. Implement data quality checks, validation rules, and monitoring processes. Troubleshoot and resolve data pipeline, database, and data lake-related issues.

Participate in data modeling, schema design, and data warehousing activities. Ensure adherence to data governance, security, and compliance standards. Mentor junior data engineers and contribute to best practices within the team.

Required Skills

and Qualifications Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field. 6+ years of experience in data engineering or related roles. Strong hands-on experience with SQL (query writing, optimization, indexing, stored procedures, performance tuning). Strong experience with Azure Data Factory (ADF) for data ingestion, transformation, orchestration, and scheduling.

Experience working with Azure Data Lake Storage (ADLS) and data lake architectures. Hands-on experience with at least one NoSQL database, preferably MongoDB. Good understanding of data analytics concepts and data preparation for reporting and BI solutions. Experience working with relational databases such as SQL Server, Azure SQL, PostgreSQL, or Oracle.

Understanding of data warehousing concepts, dimensional modeling, and ETL best practices. Experience with Azure services such as Azure Data Lake, Azure Blob Storage, Azure Synapse Analytics, or Azure SQL Database is preferred. Strong analytical and problem-solving skills. Excellent communication and stakeholder management skills.

Preferred Qualifications

Experience with Power BI or other BI/reporting tools. Exposure to Python or Py. Spark for data processing is an added advantage. Experience working in Agile/Scrum delivery environments. Microsoft Azure Data Engineer certification is a plus. Key Competencies Data Engineering SQL Development & Performance Tuning Azure Data Factory Azure Data Lake MongoDB / NoSQL Databases Data Integration Data Analytics Support Data Warehousing Problem Solving Collaboration & Communication