Staff Data Engineer - Python (6-10 yrs)

Job Title : Staff Data Engineer

Experience : 5-8 Years

Job Location : Hyderabad (Hybrid work mode)

Notice period : Immediate to 30 Days (if serving notice then LWD should be 45Days max)

Requirements :

- 4+ years of experience in ETL development, data pipeline engineering, or data warehouse management.

- Strong proficiency in SQL (PostgreSQL, MySQL, or similar) for data manipulation and optimization.

- Experience with data pipeline tools (e.g., Apache Airflow, AWS Glue, dbt, or similar).

- Hands-on experience with cloud-based data platforms (e.g., AWS Redshift, Snowflake, Big Query, or Azure Synapse).

- Knowledge of data modeling, data warehousing concepts, and performance tuning.

- Experience working with structured and semi-structured data formats (JSON, Parquet, Avro,

etc.).

- Proficiency in Python or another scripting language for data automation and transformation.

- Strong problem-solving and troubleshooting skills.

- Excellent communication skills and ability to work with both technical and non-technical

stakeholders.

- Experience working in Agile development practices and delivering iterative solutions.

Nice to Have :

- Experience with orchestration tools like Apache Airflow or Prefect.

- Familiarity with real-time data streaming (Kafka, Kinesis, or similar).

- Knowledge of NoSQL databases (MongoDB, DynamoDB, etc.).

- Experience with CI/CD pipelines for data engineering workflows.

- Certifications in AWS, Azure, GCP or relevant data engineering technologies.

Responsibilities :

- Design, develop, and maintain scalable ETL pipelines to support data integration and analytics needs.

- Build, optimize, and manage data pipelines and workflows to ensure efficient data movement and transformation.

- Monitor and troubleshoot data pipeline performance, ensuring data reliability and accuracy

- Maintain and optimize data warehouse architecture, ensuring efficient storage and data retrieval.

- Work with large, complex datasets to support analytical and business intelligence needs.

- Define, execute, and optimize SQL queries for data transformation and extraction.

- Collaborate with Business Intelligence, Data Analytics, and Engineering teams to ensure data

accessibility and performance.

- Automate data ingestion, processing, and refresh schedules to maintain up-to-date datasets.

- Implement data governance, security, and compliance best practices.

- Continuously evaluate and adopt new technologies to improve data infrastructure.