Role & responsibilities

- Provide technical recommendations and evaluate project feasibility and workloads.
- Design and implement efficient pipeline architectures for data ingestion, transformation, and storage.
- Develop modular, efficient code for data transformation and integration, ensuring adherence to modern development practices.
- Perform data ingestion from source systems, including ETL processes, when tables are not available on the data platform.
- Conduct regular pipeline maintenance and upgrades, troubleshooting and resolving issues to ensure optimal performance.

- Implement data quality testing (automatic) and validation to maintain high standards of data integrity and reliability

Preferred candidate profile

- Expert knowledge in dbt, SQL, Python,



Spark (PySpark), Git, Azure DevOps and Databricks.
- Expertise in cloud engineering (e.g., AWS, Azure); experience with infrastructureascode is a plus, and deploying CI/CD pipelines is a must.
- Solid problemsolving skills.
- 5 years of experience in creating and maintaining data pipelines.
- Experience handling scientific datasets for cheminformatics or bioinformatics (e.g., microbiome) is a plus.
- Experience with FAIR data principles, data governance, and data standards commonly used in scientific domains.

📌 Expert Data AI Engineer-DSM-Firmenich -Hyderabad
🏢 DSM Firmenich
📍 Hyderabad