Wawa’s enterprise data platform is evolving with an AI-augmented delivery model, and this Senior Data Engineer role focuses on designing and building reliable data solutions that serve the business. You will work across pipeline development, data product certification, and production issue resolution, helping ensure correctness, quality, cost control, and standards compliance.
What you’ll do
- Design, build, optimize, and maintain data pipelines that ingest structured and semi-structured data in both real time and batch, delivering it into Wawa’s Raw, Refined, and Data Product layers with scalability, repeatability, security, and user-ready service.
- Address moderately complex data problems by translating business needs into technical requirements and designs, and contribute to end-to-end designs for more complex initiatives.
- Apply data modeling standards across business intelligence tools, including designing data structures for moderately complex solutions and evaluating the suitability and quality of candidate data sets.
- Build and deliver data products that meet documented quality SLAs, 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 adherence to production policies.
- Validate upstream data against defined quality rules, and when failures occur, produce a preliminary root-cause summary.
- Collaborate with Analytics and Data Science to deliver tested, reliable data services that support self-service while keeping solutions consistent.
- Follow security standards for all data and tools introduced to the team.
- Support technical direction through design reviews, mentoring junior engineers, suggesting improvements to development and system standards, and investigating and resolving production data issues.
- Work with the Lead Data Engineer to align business requirements with technical feasibility for new projects.
Required 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 experience with 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 (SQL, stored procedures, tasks, streams, 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 track record working with interrelated systems and integrating data 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, catch defects, apply standards, and provide actionable feedback.
- Experience in an AI-augmented or agent-assisted development environment, or strong aptitude for it, including directing AI coding agents, reviewing their output, and taking accountability for what ships.
AI-augmented delivery model
- Use Wawa’s AI coding harness and curated skills as the default way of working by directing agents to draft pipelines, stored procedures, data models, and tests rather than writing every artifact from scratch.
- 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 agents can produce correct, standards-compliant work, and determine when work should be done by hand.
- Verify agent output against Wawa data architecture standards, conformance rules, and review gates before moving to production.
- Surface recurring engineering patterns to the platform team so they can be codified into reusable agent skills.
Tools and technologies
Snowflake, Python, SQL, stored procedures, tasks, streams, dynamic tables, AWS, Monte Carlo, Great Expectations
Location: Media, PA (onsite)
Wawa will provide reasonable accommodation to complete an application upon request, consistent with applicable law. To request an accommodation, contact asc@wawa.com.
