Senior Data Engineer

Wawa is building scalable, production-ready data capabilities on its enterprise data platform, and this role supports that mission using an AI-augmented delivery model. As a Senior Data Engineer, you will design and operate data pipelines and certified data products, with an emphasis on correctness, quality, cost control, and compliance. You will also mentor teammates and partner across Data Governance, Analytics, and Data Science to keep solutions reliable and consistent.

What you will do

• Design, build, optimize, and maintain data pipelines that move structured and semi-structured data in both real time and batch into Wawa’s Raw, Refined, and Data Product layers.
• Solve moderately complex data problems by translating business needs into technical requirements, designs, and end-to-end solutions.
• Apply data modeling standards across business intelligence tools, design data structures for moderately complex solutions, and assess the suitability and quality of candidate datasets.
• Build and deliver data products that meet documented quality SLAs, including lineage and ownership requirements.
• Develop and maintain Snowflake-native transformation pipelines using SQL, stored procedures, tasks, streams, and dynamic tables, with version control, testing, and CI/CD-gated deployments.
• Optimize warehouse cost and performance through query tuning, warehouse sizing, and consumption monitoring.
• Partner with Data Governance on certification reviews, quality remediation, and policy adherence for production datasets.
• Validate upstream data against defined quality rules, and when failures occur, provide a preliminary root-cause summary.
• Collaborate with Analytics and Data Science to deliver tested, reliable data services for self-service while keeping solutions consistent.
• Follow security standards for all data and tools introduced to the team.
• Support production data issue investigation and resolution, participate in design reviews, and mentor junior engineers while improving development and system standards.
• Work with the Lead Data Engineer to balance business requirements with technical feasibility on new projects.

What you bring

• 5+ years of database and data integration experience.
• 3+ years implementing data models (logical, physical, and dimensional), including entity relationship modeling and exposure to data warehouse design.
• 3+ years building Enterprise Data & Analytics solutions on a modern cloud data platform; Snowflake required.
• Strong knowledge of Python and SQL, including experience implementing data solutions with open-source technologies.
• Hands-on experience building Snowflake-native transformation pipelines using SQL, stored procedures, tasks, streams, and dynamic tables in an AWS-hosted cloud environment.
• Experience operating Snowflake at scale, including warehouse sizing, cost monitoring, query optimization, and access control.
• Experience implementing a range of data pipeline patterns and strategies.
• Strong knowledge of data security principles and a proven ability to work with interrelated systems to bring data together on enterprise platforms.
• Familiarity with data observability and quality tooling (e.g., Monte Carlo, Great Expectations, Snowflake data quality monitors) and applying it to certification SLAs.
• Ability to review code critically, catch defects, apply standards, and provide actionable feedback.
• Experience in an AI-augmented or agent-assisted development environment, including comfort directing AI coding agents, reviewing outputs critically, and remaining accountable for what ships.
• A Bachelor’s degree in Computer Science/Engineering is preferred.

AI-augmented delivery approach

• Use Wawa’s AI coding harness and curated skills as the default workflow to draft pipelines, stored procedures, data models, and tests rather than hand-writing every artifact.
• Review, correct, and own agent-produced code and designs to the same standard as your own work.
• Write precise specifications, prompts, and acceptance criteria so an agent can produce correct, standards-compliant artifacts, including deciding when a task is better done by hand.
• Verify agent output against Wawa data architecture standards, conformance rules, and review gates before production deployment.
• Surface recurring engineering patterns to the platform team so they can be codified into reusable agent skills.

Technologies

• Snowflake, Python, SQL, stored procedures, tasks, streams, dynamic tables, AWS
• Monte Carlo, Great Expectations

Essential functions: manage multiple priorities simultaneously; collaborate with cross-functional teams and build strong relationships with business partners; communicate effectively; contribute with a “can do” attitude in a fast-paced environment; read code critically and specify work precisely enough to direct both people and AI coding agents; help maintain data strategy standards across the data team’s work.

Accommodation: Wawa will provide reasonable accommodation to complete an application upon request, consistent with applicable law. If you require an accommodation, contact [email protected].