
Data Engineer- AI/ML
3 days ago
Role & responsibilities
Implement ML and Generative/Agentic AI solutions to optimize Data Governance processes.
Design, develop, and maintain scalable data pipelines using Python, PySpark, and Databricks.
- Develop automation frameworks to support data quality, lineage, classification, and access control.
- Develop and deploy machine learning models to uncover data patterns, detect anomalies, and enhance data governance and privacy compliance
- Collaborate with data stewards, analysts, and governance teams to build self-service data capabilities.
- Work with Databricks, Azure Data Lake, AWS, and other cloud-based data platforms for data engineering.
- Build, configure, and integrate APIs for seamless system interoperability.
- Ensure data integrity, consistency, and compliance across systems and workflows.
- Integrate AI models to support data discovery, metadata enrichment, and intelligent recommendations.
- Optimize data architecture to support analytics, reporting, and governance use cases.
- Monitor and improve the performance of ML/AI components in production environments.
- Stay updated with emerging AI and data engineering technologies to drive continuous innovation.
Technical Skills:
- Strong programming skills in Python, PySpark, SQL for data processing and automation.
- Experience with Databricks and Snowflake (preferred) for building and maintaining data pipelines.
- Experience with Machine Learning model development and Generative/Agentic AI frameworks (e.g. LLMs, Transformers, LangChain) especially in the Data Management space
- Experience working with REST APIs & JSON for service integration
- Experience working with cloud-based platforms such as Azure, AWS, or GCP
- Power BI dashboard development experience is a plus.
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