Python Data Engineer.
This mandate is run by SYMPHONI HR, a Mumbai-based executive search firm, est. 2003. Applications are email-verified and reach the search team running the role — confidentially, always.
About the organisation.
We are partnering with a leading global computer software firm that specializes in digital transformation and data modernization services. The organization is known for its commitment to innovation and its collaborative, fast-paced culture that empowers engineers to solve complex technical challenges for enterprise clients.
About the role.
This role is for an experienced Python Data Engineer to lead a large-scale migration program from legacy SAS environments to Google Cloud Platform. You will be responsible for analyzing complex transformation logic, building scalable ETL/ELT pipelines, and ensuring data integrity throughout the migration process.
What you will do.
- Analyze existing SAS datasets, macros, and PROC SQL logic to translate them into modern Python, SQL, and DBT models.
- Develop and maintain scalable data pipelines using Google Cloud Platform services including BigQuery, Cloud Composer, and Dataflow.
- Build reusable Python frameworks for data ingestion, validation, and reconciliation between legacy and cloud environments.
- Implement automated data quality checks using frameworks like Great Expectations and Pytest.
- Optimize SQL queries and BigQuery tables to ensure high performance and cost efficiency.
- Collaborate with cross-functional teams including data architects and business analysts to document technical conversion rules.
- Support the full software development lifecycle, including CI/CD processes, unit testing, and production deployment.
What you bring.
- 4–6 years of professional experience in data engineering and ETL/ELT pipeline development.
- Strong proficiency in Python and advanced SQL.
- Hands-on experience with DBT and Google BigQuery.
- Proven experience in data migration projects, specifically involving SAS to cloud transitions.
- Solid understanding of PySpark, Pandas, NumPy, and PyArrow.
- Experience with orchestration tools like Airflow or Cloud Composer.
- Knowledge of dimensional modeling, data warehousing concepts, and star schema design.
- Familiarity with Infrastructure as Code tools such as Terraform.
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