Senior Data Pipeline Specialist

About Us:

We're a leading provider of telenutrition and foodcare solutions. Our platform empowers healthier food choices, drives lasting behavior change, and delivers long-term health outcomes.

Our highly personalized digital platform guides users on a tailored journey to eating well while saving time and money.

We integrate dietary assessments and nutrition counseling with online food ordering and cost-effective meal planning for the entire family. Our platform optimizes ingredients both at home and on the go.

We partner with national and regional retailers across the U.S., making healthier food more accessible. We also assist users with SNAP enrollment and management, providing tangible access to nutritious food.

At our organization, our mission is to make nutritious food accessible and affordable for everyone. We're committed to a set of core values that shape our culture and work environment:

• Measured: We make data-driven decisions.
• Impactful: We strive to achieve our mission and vision.
• Collaborative: We help each other succeed.
• Hungry: We maintain a growth mindset, seeking to overcome challenges with courage.
• Joyful: We take joy in each other, our work, and the privilege of doing this work.

The Senior Data Engineer plays a critical role in constructing and optimizing our data pipeline architecture. They collaborate closely with data scientists and analysts to facilitate data-related functionalities.

The ideal candidate will:

• Lead the optimization and scalability of data delivery pipelines, ensuring performance and reliability for cross-functional stakeholders.
• Architect, build, and maintain robust, high-throughput data pipelines and infrastructure to support advanced analytics and machine learning.
• Partner with data architects, data scientists, and analysts to design solutions that meet evolving data requirements and business objectives.
• Establish best practices for data quality, governance, security, and compliance; implement automated frameworks for cleaning, validation, correction, and enrichment.
• Drive continuous improvement in data engineering processes by identifying bottlenecks, reducing manual effort through automation, and advancing scalability standards.
• Mentor junior engineers, provide technical guidance, and influence broader data platform strategy.

The ideal candidate should be:

• A proactive leader who drives efficient data delivery, infrastructure evolution, and technical excellence.
• Quality-oriented, with a strong sense of ownership over data reliability and accessibility.
• Experienced in applying secure, compliant data handling practices in regulated environments.
• Collaborative and skilled at bridging business needs with technical solutions, supporting stakeholders at all levels.
• An expert in data warehouse architecture, dimensional modeling, and automated data engineering at scale.

The ideal candidate has:

• 6+ years of professional experience in data engineering, with a proven track record of leading large-scale, complex projects.
• Deep expertise in modern cloud data warehouses (Snowflake, Redshift, or BigQuery).
• Advanced SQL skills and strong experience with relational and columnar database systems.
• Proficiency in data pipeline/workflow orchestration tools (e.g., Apache Airflow, Dagster, Luigi).
• Solid programming background (Python, Scala, or Java) for data processing and automation.
• Experience designing data models and schemas for both operational and analytical use cases.
• Strong analytical and problem-solving skills, thriving in fast-paced, high-growth environments.
• Familiarity with healthcare data standards (FHIR, HL7) or other regulated data domains is a plus.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field (Master's degree preferred).