- Design, build and maintain scalable data pipelines for integrating diverse data sources.

- Implement and manage scalable data architectures and infrastructure to support analytics.

- Collaborate with data scientists, ML engineers, and product teams to enable seamless data flow for AI/LLM- driven use-cases.

- Develop and optimize ETL processes for continuous data ingestion and transformation.

- Ensure data quality, integrity, and security, including anonymization and access controls.

- Support the development of interactive dashboards and query-assist tools for business users.

- Contribute to the feedback loop for continuous improvement of data-driven insights.

- Deploy and monitor pipelines on AWS cloud and/or edge infrastructure.

You are a successful candidate if you have :

- strong experience with data engineering tools and frameworks (e.g., Python, SQL, Spark, Airflow).

- Hands-on experience with cloud data platforms (AWS, Azure, or GCP).

- Familiarity with federated data architectures and large-scale data integration.

- Experience working with both structured and unstructured data.

- Knowledge of data privacy, security best practices, and compliance (anonymization, access control, audits).

- The ability to work in cross-functional teams (data scientists, ML engineers, product managers).

- Experience in automotive, marketing analytics, or customer intelligence domains is a plus.

- Exposure to AI/LLM-based systems

- Experience with dashboarding tools (Power BI, Tableau, or similar).

- Familiarity with DevOps/SecOps practices for data infrastructure