ETL Developer - AI/ML Integration (Hybrid)

At Broadridge, we've built a culture where the highest goal is to empower others to accomplish more. If you're passionate about developing your career, while helping others along the way, come join the Broadridge team.

We are seeking a skilled Data Engineer / ETL Developer specializing in AI/ML integration to join our dynamic data engineering team. This role demands hands-on expertise in designing and optimizing end-to-end data integration pipelines, with a focus on leveraging AI/ML technologies to advance data mapping and workflow automation on enterprise data platforms.

Responsibilities

• Architect, build, and optimize scalable ETL workflows and data models for high-volume, high-performance analytics environments.
• Integrate AI/ML solutions and automation tools to streamline and accelerate data mapping, transformation, and ETL processes across diverse enterprise projects.
• Collaborate closely with Clients, business stakeholders, and cross-functional technical teams to document data mapping requirements ensure data accuracy, and optimize workflows.
• Author and maintain comprehensive documentation, including data architecture diagrams, data flow lineage, mapping specifications, and reusable component repositories.
• Institute standardization practices for data mapping, enforce naming conventions, and promote reuse of modular ETL assets.
• Partner with data engineering and AI/ML teams to ensure effective integration of ETL pipelines with machine learning workflows and feature stores.
• Continuously evaluate and optimize ETL processes for efficiency, reliability, scalability, and alignment with evolving data strategies and technologies.
• Provide expert guidance for system integration, data migration, troubleshooting, and performance tuning to maintain data accuracy, quality, and operational excellence.
• Stay abreast of emerging trends in cloud data platforms (especially AWS), data modeling practices, and AI/ML innovations to drive continuous improvement across the data landscape.

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a closely related field.
• 5+ years' experience in data engineering, data modeling, or database design for enterprise environments.
• Advanced proficiency with data modeling tools (e.g., Erwin, ER/Studio, dbt) and strong command of SQL and relational databases (Oracle, SQL Server, MySQL, PostgreSQL).
• Hands-on experience developing and maintaining ETL pipelines using industry-standard tools (Informatica, Talend, SSIS) and scripting (Python, Scala).
• Experience with cloud-based data warehouses (Snowflake, Redshift, Azure Synapse, BigQuery) and exposure to big data technologies.
• Solid foundation in data governance, data quality management, and metadata management principles.
• Exceptional analytical, organizational, and communication skills, with a proven ability to bridge technical and business domains.
• Demonstrated experience supporting AI/ML initiatives (e.g., enabling feature stores, integrating data science workflows, supporting model serving/pipelines).

• Experience with NoSQL databases and semi-structured data (e.g., MongoDB, Cassandra, DynamoDB).
• Familiarity with cloud-native ETL and orchestration tools.
• Proficiency in data integration scripting (Python, Scala) and ML-related data processing libraries.
• Understanding of Agile/Scrum methodologies and practices.
• Relevant certifications in data modeling, cloud platforms (e.g., AWS Database Specialty, Snowflake), or data management.
• Exposure to MLOps, feature engineering, and end-to-end AI/ML solution delivery.