About the Opportunity

This role is responsible for designing and delivering scalable, high quality data solutions that enable enterprise analytics and reporting at Driscoll’s. The position combines hands on data engineering with technical leadership, ensuring data pipelines, models, and curated datasets are reliable, performant, and aligned with platform architecture and enterprise standards.

The role serves as a key technical partner across business, analytics, platform, security, and DevOps teams, translating complex requirements into production ready solutions while supporting data governance, quality, observability, and cost optimization initiatives. It also acts as an escalation point for complex data issues and contributes to design and code reviews to promote engineering best practices.

 

Responsibilities

• Design, build, and deliver complex data solutions aligned with existing platform architecture and enterprise standards.
• Participate in and contribute to design and code reviews, providing constructive feedback and technical guidance to peers.
• Develop and operate ETL / ELT pipelines using AWS services such as Glue, Spark, Athena, Redshift, S3, Lambda, SQS, and DMS.
• Serve as a technical escalation point for complex data pipeline and analytics issues, supporting root-cause analysis and remediation.
• Translate business and analytics requirements into well-structured and documented data models, transformations, and curated datasets.
• Identify and implement performance, scalability, and cost‑optimization improvements within data pipelines and analytics workloads.
• Implement and maintain data quality checks and controls to ensure accuracy, completeness, and consistency.
• Support and collaborate with offshore engineers by clarifying requirements, reviewing work, and reducing delivery friction.
• Embed observability, logging, monitoring, and alerting into data pipelines and analytics datasets.
• Contribute to the adoption of data governance, lineage, and quality practices across the data platform.
• Collaborate closely with platform, DevOps, security, architecture, integration, application and analytics teams.
• Partner with vendors during design and delivery phases, supporting stabilization and production readiness.
• Promote and follow engineering best practices for code quality, testing, documentation, and operational support.
• Support enterprise reporting using Tableau backed by Redshift, Athena, or Lakehouse architecture.

   

Candidate Profile