Senior Data Engineer

Wawa, Inc.

About The Position

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. For complex solutions, the engineer assists the Lead Data Engineer with design and builds major components. The role 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 work precisely, directs AI coding agents to draft pipelines, procedures, and data products, then reviews, corrects, and takes full ownership of the deliverables. The role is accountable for the correctness, quality, cost, and standards compliance of all output, whether written by hand or produced with agents. It also contributes to technical direction through design and code reviews, mentors junior engineers, and supports resolution of production data issues. The engineer builds and maintains scalable, secure, repeatable data pipelines and Snowflake-native transformations; develops certified data products; supports data modeling, quality, governance, security, and cost/performance optimization; and collaborates with Analytics, Data Science, Data Governance, and business partners. The role follows Wawa’s AI coding harness and curated skills as the default approach, while critically validating agent output against architecture standards, conformance rules, and review gates before production.

Requirements

5+ years of database and data integration experience.
3+ years implementing logical, physical, and dimensional data models, including entity relationship modeling and exposure to data warehouse design.
3+ years developing Enterprise Data & Analytics solutions on a modern cloud data platform; Snowflake is required.
Strong knowledge of Python and SQL, and 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 experience working with interrelated systems and integrating their data on enterprise platforms.
Ability to review code critically, catch defects, apply standards, and provide actionable feedback.
Ability to read code critically and specify work precisely enough to direct people and AI coding agents.
Excellent communication skills, ability to handle multiple priorities, and ability to build strong, trusting relationships with business partners.
Bachelor’s degree in Computer Science or Engineering is preferred.

Nice To Haves

Familiarity with data observability and quality tooling such as Monte Carlo, Great Expectations, or Snowflake data quality monitors, and applying these tools to certification SLAs.
Experience working in an AI-augmented or agent-assisted development environment, or clear aptitude for one, including comfort directing AI coding agents, critically reviewing their output, and remaining accountable for what ships.

Responsibilities

Design, build, optimize, and maintain pipelines ingesting structured and semi-structured data in real time and batch into Wawa’s Raw, Refined, and Data Product layers.
Solve moderately complex data problems, translate business needs into technical requirements and designs, and contribute to end-to-end designs for complex work.
Apply data modeling standards, design data structures for moderately complex solutions, and assess candidate data sets for suitability and quality.
Build and deliver data products that meet documented quality SLAs, lineage, and ownership requirements.
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 on certification reviews, quality remediation, and policy adherence for production datasets.
Validate upstream data against defined quality rules and provide a preliminary root-cause summary when validation fails.
Collaborate with Analytics and Data Science to build tested, reliable data services that enable self-service and consistency.
Follow security standards for all data and tools introduced to the team.
Participate in design reviews, mentor junior engineers, and suggest improvements to development and system standards.
Support investigation and resolution of production data issues.
Work with the Lead Data Engineer to balance business requirements and technical feasibility on new projects.
Use Wawa’s AI coding harness and curated skills to direct agents to draft pipelines, stored procedures, data models, and tests.
Review, correct, and own agent-produced code and designs to the same standard as work produced independently.
Write precise specifications, prompts, and acceptance criteria for AI-assisted work, and determine when tasks are better completed by hand.
Verify agent output against Wawa’s data architecture standards, conformance rules, and review gates before production.
Surface recurring engineering patterns to the platform team for codification into reusable agent skills.
Handle multiple priorities simultaneously and collaborate with cross-functional teams and business partners.
Help maintain data strategy standards across the data team.