Senior Data Engineer

Job Description

Job Title: Senior Data Engineer, AI              Location: Corporate

Department: Information Technology         

Job Summary:  The Senior Data Engineer, AI designs and develops scalable data solutions of moderate complexity on Wawa's enterprise data platform, working in an AI-augmented delivery model. On complex solutions, the engineer assists the Lead Data Engineer with design and builds major components. The individual uses modern data platforms, Snowflake-native tooling, and an AI coding harness with curated skills to design, build, and test data pipelines and certified data products. The engineer specifies the work precisely, directs AI coding agents to produce a first draft of pipelines, procedures, and data products, then reviews, corrects, and takes full ownership of what ships. Accountable for the correctness, quality, cost, and standards compliance of all output, whether hand-written or agent-produced. Contributes to technical direction through design and code reviews, mentors junior engineers, and supports the resolution of production data issues.

Principal Duties:

• Design, build, optimize, and maintain data pipelines that ingest structured and semi-structured data, in real time and batch, into Wawa's Raw, Refined, and Data Product layers, ensuring they are scalable, repeatable, secure, and serve users across the company.

• Solve moderately complex data problems, translate business needs into technical requirements and designs, and contribute to end-to-end solution designs for complex work.

• Apply data modeling standards across business intelligence tools, design data structures for moderately complex solutions, and assess the suitability and quality of candidate data sets.

• Build and deliver data products that meet their documented quality SLAs, lineage, and ownership requirements.

• Build and maintain Snowflake-native transformation pipelines (SQL, stored procedures, tasks, streams, 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 on certification reviews, quality remediation, and policy adherence for production datasets.

• Validate data received from upstream systems against defined quality rules, and produce a preliminary root-cause summary when it fails.

• Collaborate with the Analytics and Data Science teams to build tested, reliable data services that enable self-service and keep solutions consistent.

• Follow security standards for all data and tools introduced to the team.

• Contribute to technical direction by participating in design reviews, mentoring junior engineers, and suggesting improvements to development and system standards. Support the investigation and resolution of production data issues.

• Work with the Lead Data Engineer to balance business requirements with technical feasibility on new projects.

AI-Augmented Delivery:

• Use Wawa's AI coding harness and its curated skills as the default way of working: direct agents to draft pipelines, stored procedures, data models, and tests, rather than hand-writing every artifact from scratch.

• Review, correct, and own agent-produced code and designs to the same standard as own work.

• Write precise specifications, prompts, and acceptance criteria that let an agent produce correct, standards-compliant work, and judge when a task is better done by hand.

• Verify agent output against Wawa's data architecture standards, conformance rules, and review gates before it advances to production.

• Surface recurring engineering patterns to the platform team so they can be codified into reusable agent skills.

Essential Functions:

• Handle multiple priorities simultaneously.

• Work collaboratively with cross-functional teams and build strong, trusting relationships with business partners.

• Excellent communication skills.

• Passion for innovation and a “can do” attitude 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.

Basic Qualifications:

• Bachelor's degree in Computer Science/Engineering preferred.

• 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 developing Enterprise Data & Analytics solutions on a modern cloud data platform, Snowflake required.

• Strong knowledge of Python and SQL; 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: 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 track record working with interrelated systems and bringing that 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.

• Demonstrated ability to review code critically, catching defects, applying standards, and giving actionable feedback. This judgment is central to the role.

• Experience working in an AI-augmented or agent-assisted development environment, or clear aptitude for one. Comfort directing AI coding agents, reviewing their output critically, and remaining accountable for what ships.

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

Wawa, Inc. is an equal opportunity employer. Wawa maintains a work environment in which Associates are treated fairly and with respect and in which discrimination of any kind will not be tolerated. In accordance with federal, state and local laws, we recruit, hire, promote and evaluate all applicants and Associates without regard to race, color, religion, sex, age, national origin, ancestry, familial status, marital status, sexual orientation or preference, gender identity or expression, citizenship status, disability, veteran or military status, genetic information, domestic or sexual violence victim status or any other characteristic protected by applicable law. Unlawful discrimination will not be a factor in any employment decision.