Senior Data Engineer

Wawa is seeking a Senior Data Engineer to design and deliver scalable, moderately complex data solutions on the enterprise data platform, using an AI-augmented delivery model. The role includes building and validating pipelines and data products, maintaining correctness and quality, ensuring compliance with standards, and mentoring teammates while resolving production data issues.

Onsite Location

Media, PA (onsite)

Role Summary

The Senior Data Engineer, AI designs and develops data pipelines and certified data products using an AI-augmented delivery model. Responsibilities span development and testing of data services across Raw, Refined, and Data Product layers, with emphasis on correctness, quality, cost controls, lineage, and compliance. The role also involves mentoring and active support for investigations tied to production data issues.

Responsibilities

• Design, build, optimize, and maintain data pipelines ingesting structured and semi-structured data in real time and batch into Raw, Refined, and Data Product layers to ensure scalability, repeatability, security, and enterprise usability.
• Solve moderately complex data problems, translate business needs into technical requirements and designs, and contribute to end-to-end solution design for complex work.
• Apply data modeling standards across business intelligence tools, design data structures for moderately complex solutions, and evaluate the suitability and quality of candidate datasets.
• Build and deliver data products that meet documented quality SLAs, lineage requirements, and ownership expectations.
• Build and maintain Snowflake-native transformation pipelines using SQL, stored procedures, tasks, streams, and dynamic tables, with version control, testing, and CI/CD-gated deployment.
• Optimize warehouse cost and performance through query tuning, warehouse sizing, and consumption monitoring.
• Partner with Data Governance for certification reviews, quality remediation, and production policy adherence.
• Validate upstream data using defined quality rules and provide a preliminary root-cause summary when validations fail.
• Collaborate with Analytics and Data Science teams to deliver tested, reliable data services that support self-service and consistent solution delivery.
• Follow security standards for data and tools introduced to the team.
• Contribute to technical direction through design reviews, mentoring junior engineers, recommending improvements to development and system standards, and supporting production issue investigation and resolution.
• Work with the Lead Data Engineer to balance business requirements with technical feasibility on new projects.

Requirements

• Bachelor’s degree in Computer Science/Engineering (preferred).
• 5+ years of database and data integration experience.
• 3+ years implementing data models, including logical, physical, and dimensional modeling; experience with entity relationship modeling and exposure to data warehouse design.
• 3+ years developing Enterprise Data & Analytics solutions on a modern cloud data platform, with 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.
• Proven ability working with interrelated systems and integrating data on enterprise platforms.
• Familiarity with data observability and quality tooling such as Monte Carlo, Great Expectations, and Snowflake data quality monitors, applied to certification SLAs.
• Demonstrated ability to review code critically, catch defects, apply standards, and provide actionable feedback.
• Experience in an AI-augmented or agent-assisted development environment, or clear aptitude for it; ability to direct AI coding agents, review their output critically, and remain accountable for what ships.

Technologies

• Snowflake
• Python
• SQL
• Stored procedures
• Tasks
• Streams
• Dynamic tables
• AWS
• Monte Carlo
• Great Expectations

AI-Augmented Delivery

• Use Wawa’s AI coding harness and curated skills as the default workflow, directing agents to draft pipelines, stored procedures, data models, and tests instead of hand-writing every artifact.
• Review, correct, and own agent-produced code and designs to the same standard as personal work.
• Write precise specifications, prompts, and acceptance criteria so agents produce correct, standards-compliant work, while deciding when work should be completed by hand.
• Verify agent output against Wawa’s data architecture standards, conformance rules, and review gates prior to production advancement.
• Surface recurring engineering patterns to the platform team so they can be converted into reusable agent skills.

Essential Functions

• Manage multiple priorities simultaneously.
• Collaborate with cross-functional teams and build strong relationships with business partners.
• Communicate effectively.
• Maintain a can-do attitude and support innovation in a fast-paced team 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.

Reasonable Accommodation

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