Senior Data Engineer

We are hiring a Senior Data Engineer to design, develop, and optimize scalable cloud data platforms and modern ETL/ELT pipelines using Microsoft Fabric, Databricks, or Snowflake.

The role involves building and maintaining data lakehouse and data warehouse solutions, developing high-performance data pipelines, enabling analytics and reporting, and contributing to data engineering best practices.

Strong hands-on experience in PySpark, SQL, Python/Scala, and cloud data platforms is required.

What You Will Do

Following are the high-level responsibilities that you will play, but are not limited to:

- Design, develop, and maintain scalable data pipelines, data models, and ETL/ELT processes.
- Build and optimize data lake, lakehouse, and data warehouse solutions using Microsoft Fabric, Databricks, or Snowflake.
- Develop data processing solutions using PySpark, Python, Scala, and SQL.
- Work with large and complex datasets to improve data processing performance, reliability, and scalability.
- Develop and maintain batch and real-time data pipelines as required.
- Implement data transformation, cleansing, validation, and integration processes.
- Work with Delta Lake, Spark, Snowflake, Microsoft Fabric, and other modern data engineering technologies.
- Support business analytics and self-service reporting through Power BI and other visualization platforms.
- Collaborate with data scientists, analysts, BI developers, and business stakeholders to deliver reliable data solutions.
- Implement data quality, governance, security, and monitoring practices across data pipelines.
- Troubleshoot and resolve data pipeline, performance,



and production issues.
- Contribute to the development of coding standards, reusable frameworks, and data engineering best practices.
- Participate in code reviews and ensure high-quality, maintainable, and scalable solutions.
- Implement CI/CD practices for data engineering workflows and deployments.
- Stay updated with emerging data engineering technologies and contribute to continuous improvement of the data ecosystem.

Required Qualifications

- Bachelor's/Master’s degree in Computer Science, Information Technology, Engineering, or a related field.
- 6–10 years of experience** in data engineering, data platform development, or related areas.

Strong hands-on experience in one or more of the following:

- Microsoft Fabric** – Data Factory, Lakehouse, Data Warehouse
- Databricks** – Spark, Delta Lake, PySpark, MLflow
- Snowflake** – Data Warehousing, Snowpipe, Performance Optimization
- Power BI** – Data Modeling, DAX, Report Development
- Strong proficiency in SQL.
- Solid programming skills in Python or Scala.
- Hands-on experience with PySpark/Apache Spark and large-scale data processing.
- Experience working with Azure, AWS, or GCP cloud data services.
- Strong understanding of data modeling, ETL/ELT concepts, data warehousing, and data lake/lakehouse architectures.
- Understanding of data governance, data quality, security, and access control.
- Experience with CI/CD, Git, and DevOps practices for data engineering workflows.
- Strong analytical and problem-solving skills.
- Ability to work independently and collaborate effectively with cross-functional teams.

📌 Senior Data Engineer (Hyderabad)
🏢 Thinkwise Consulting
📍 Hyderabad