Data Product Engineer

The Data Product Engineer is responsible for designing, developing, and operating scalable, reusable, and trusted data products that power business intelligence, advanced analytics, AI/ML solutions, and operational decision-making. This role combines modern data engineering practices with product thinking to build high-quality data assets that are discoverable, governed, and reusable across the enterprise. The engineer partners with business stakeholders, product managers, architects, data scientists, and platform teams to deliver data products that align with strategic business outcomes. 

Roles & Responsibilities

• Design, develop, deploy, and maintain enterprise data products and reusable data assets.

• Build scalable batch, streaming, and event-driven data pipelines.

• Create domain-oriented data products that support analytics, reporting, operational processes, and AI initiatives.

• Develop semantic models and curated datasets to enable self-service analytics capabilities. 

• Design and optimize ETL/ELT pipelines for structured, semi-structured, and unstructured data.

• Integrate data from enterprise platforms, APIs, and cloud-based systems.

• Implement scalable ingestion, transformation, and orchestration frameworks.

• Build resilient solutions that support enterprise-scale data processing and consumption. Implement data quality validation, observability, monitoring, and remediation processes.

• Ensure data accuracy, completeness, timeliness, consistency, and reliability.

• Partner with governance teams to establish metadata and lineage practices.

• Develop solutions using modern cloud platforms such as Azure, AWS, or similar environments.

• Leverage data platforms such as Snowflake, Databricks, Synapse, Fabric, Redshift, or BigQuery.

• Optimize platform performance, scalability, resilience, and cost efficiency.

• Implement secure access controls and data protection standards.

• Support regulatory, audit, and risk management requirements. 

• Contribute to data cataloging, metadata management, and lineage 

• Implement CI/CD pipelines and DevOps/DataOps best practices.

• Create technical documentation, architectural diagrams, support guides, and operational runbooks.

• Participate in Agile ceremonies and continuous improvement initiatives.

Experience / Qualifications

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, Software Engineering, or related field.

• 5+ years of experience in Data Engineering, Analytics Engineering, Data Product Development, or related disciplines.

• Strong SQL expertise and proficiency in Python, Scala, Java, or similar development languages.

• Experience building modern ETL/ELT pipelines and data integration solutions.

• Hands-on experience with Azure, AWS, or cloud-native data platforms.

• Experience with Snowflake, Databricks, Microsoft Fabric, Synapse, Redshift, BigQuery, or equivalent platforms.

• Strong understanding of Data Modeling, Data Warehousing, Metadata Management, Data Quality, Cloud Architecture, Experience with Git, CI/CD pipelines, and Agile methodologies.  

  Shift Timings - 11 AM - 8 PM

  Location - Chennai 

  Location expectations
  This role requires working from a U.S. Bank location three (3) or more days per week