Senior Data Engineer

About the role

You will architect and own the core data pipeline infrastructure that powers Foodsmart's mission of making nutritious food accessible and affordable for everyone. You will design and build highly scalable data pipelines that ingest, transform, and deliver trusted data to support our national network of Registered Dietitians and members across employer plans and government programs. In this role, you will collaborate daily with data scientists, analysts, and product teams to turn complex business requirements into resilient, production-grade data solutions. You will be responsible for optimizing data delivery performance, ensuring data quality, and automating operational processes to reduce manual overhead. You will evaluate new technologies and contribute to strategic decisions that shape our data platform roadmap. You will implement monitoring and alerting to maintain system reliability and enable rapid troubleshooting. Ultimately, your work will directly support personalized nutrition care, behavior change tools, and food benefits that improve health outcomes for millions of members.

Key facts

What you'll do

Design, build, and maintain scalable data pipelines that consolidate structured and unstructured data from diverse sources across the Foodsmart ecosystem.

Implement robust data ingestion frameworks using modern protocols and patterns to support high-throughput, low-latency data movement.

Collaborate with data scientists and business analysts to refine data models, ensuring datasets align with analytical and operational requirements.

Optimize query performance and data delivery mechanisms to enable fast, reliable access for reporting and machine learning workloads.

Automate data validation and quality checks to detect anomalies, prevent corruption, and maintain consistency across datasets.

Develop monitoring, logging, and alerting solutions to provide visibility into pipeline health, performance, and failure scenarios.

Partner with cross-functional teams to translate business needs into technical specifications and data product requirements.

Lead the implementation of data governance practices, including metadata management, documentation, and access controls.

Integrate with cloud platforms and third-party services to support secure data sharing and compliance with regulatory standards.

Refactor legacy pipelines to improve maintainability, scalability, and cost-efficiency using infrastructure-as-code principles.

Conduct code reviews and pair programming sessions to elevate engineering standards and knowledge sharing.

Contribute to the design of data architectures that support real-time and batch processing across the organization.

Define and track data SLAs to ensure reliability, availability, and timely delivery of critical data assets.

Mentor junior engineers by providing technical guidance, feedback, and best practices for building scalable data solutions.

Requirements

Must have a Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.

Must have 6+ years of professional experience in data engineering or a closely related role with demonstrable impact.

Must have deep expertise in SQL and proficiency writing complex queries across multiple database systems.

Must have hands-on experience building data pipelines using Python and at least one major framework such as Apache Airflow or similar orchestration tools.

Must have proven experience working with relational databases and data warehousing concepts, including modeling, indexing, and optimization.

Must be comfortable working in cloud environments, with strong understanding of infrastructure, networking, and security best practices.

Must have experience implementing monitoring, logging, and alerting for data pipelines and related services.

Must demonstrate strong problem-solving skills, attention to detail, and the ability to debug complex data issues in production environments.

Must be comfortable collaborating with cross-functional stakeholders, including product managers, data scientists, and business analysts.

Must have excellent written and verbal communication skills to articulate technical concepts to both technical and non-technical audiences.

Must be self-motivated, disciplined, and able to manage multiple priorities in a fast-paced, dynamic environment.

Must be legally authorized to work in the United States without sponsorship now or in the future.

Nice to have

Experience with modern data platforms, data lakes, and cloud data warehouse solutions such as Snowflake, BigQuery, or Redshift.

Familiarity with containerization and orchestration tools such as Docker and Kubernetes.

Knowledge of data visualization tools and practices, including integration with BI platforms.

Experience with version control workflows for data engineering, including data lineage and testing frameworks.

Understanding of privacy and compliance considerations related to handling personal health information.

Practical notes

This is a full-time remote position based in the United States.

Candidates must be available during standard business hours for collaboration with US-based teams.

No sponsorship is available for this role at this time.