Data Architect

Company: Bitewell
Location: San Francisco
Posted on: April 23, 2025

Job Description:

Data ArchitectApplicants must have permanent work authorization in the United States. Bitewell is unable to provide visa sponsorship or support visa transfers for this position.Are you a data architecture visionary ready to build the systems that will revolutionize how millions understand food health?Bitewell is seeking a highly technical and visionary Data Architect to lead the design, implementation, and governance of our core data infrastructure. As the business evolves into one whose primary asset is a deep, extensible, and authoritative data corpus, this role is central to engineering the systems, flows, and validation regimes that will power our data ecosystem.The ideal candidate will possess a deep command of data architecture fundamentals - including data modeling, pipeline construction, lineage tracking, observability, and schema evolution - and will bring an engineer's mindset to problems of scale, governance, and automation. You will define how data flows, how it is structured, validated, and made trustworthy across every component of the enterprise.About BitewellOur vision is to create a world without diet-related disease. We're making this happen through our core product: The FoodHealth Score. The score is our proprietary, first-of-its-kind nutrition scoring system that combines cutting-edge science with innovative technology to give consumers insight and transparency into the healthfulness of food. We bring this to market with our partners in food retail, manufacturing, and data, which empowers customers to make healthier choices, merchandisers to stock healthier shelves and brands to make healthier products.What You'll Do

• Data Flow & Infrastructure Architecture
  • Design and document source-to-consumption data flows, including data ingress from external APIs, internal services, user-facing applications, and machine learning pipelines.
  • Architect modular, scalable data pipelines for ingestion, transformation, and loading, enabling traceability and reusability at every stage.
  • Define and implement data provenance protocols, capturing metadata and lineage across all processing layers.
  • Engineer streaming and batch processing systems using tools such as Apache Kafka, Apache Beam, or Airflow/Dbt, ensuring event ordering and idempotency.
  • Schema & Corpus Design
    • Model normalized, distributed data schemas that preserve data integrity and avoid redundancy across domains.
    • Lead the definition and maintenance of a canonical data model and schema registry to unify internal data representations.
    • Develop strategies for schema evolution that support backward/forward compatibility across dependent systems.
    • Validation & Observability
      • Define and implement data validation frameworks - including schema conformance, missingness detection, statistical anomaly detection, and referential integrity enforcement.
      • Design and deploy data observability platforms with SLAs around freshness, completeness, and accuracy.
      • Build automated audit and reconciliation processes to identify and alert on pipeline regressions or integrity violations.
      • Lineage, Governance & Metadata Management
        • Implement end-to-end data lineage tracking (both static and dynamic) across ingestion, transformations, and delivery pipelines.
        • Collaborate with Security and Compliance teams to enforce data governance policies, including retention, access control, and PII masking where applicable.
        • Establish a metadata layer (technical + business) that underpins data discoverability and semantic context for consumers.
        • Team Enablement & Documentation
          • Champion internal data standards and best practices, mentoring engineers on principled data design and pipeline development.
          • Write technical specifications, data contracts, lineage diagrams, and architecture documentation consumable by both engineering and business stakeholders.
          • Serve as a cross-functional bridge between data engineering, software, product, analytics, and machine learning teams.Who You Are
            • 7+ years experience in Data Architecture, Data Engineering, or a similar backend-focused discipline.
            • Mastery of SQL, data modeling (3NF, star/snowflake, dimensional modeling), and ETL/ELT frameworks.
            • Proven experience with distributed data systems (PostgreSQL, BigQuery, Snowflake, Redshift, Delta Lake, etc.).
            • Deep knowledge of data pipeline orchestration tools (Airflow, Dagster, Prefect) and transformation layers (dbt, Spark, Flink).
            • Experience building data quality systems (e.g., Great Expectations, Soda, Deequ) and schema validation engines.
            • Fluency in metadata and lineage tools (OpenLineage, DataHub, Amundsen, Marquez).
            • Expertise in observability tooling (e.g., Monte Carlo, Datadog, Grafana, OpenTelemetry for data).
            • Comfort with containerized environments (Docker, Kubernetes) and infrastructure-as-code (Terraform, Pulumi).
            • Familiarity with event-driven architecture and streaming data frameworks (Kafka, Pulsar, Kinesis).
            • Strong documentation and systems design skills with a bias for clarity, versioning, and reproducibility.Added BonusPreferred Qualifications
              • Experience building data platforms in health, food, e-commerce, or scientific domains.
              • Familiarity with semantic layer modeling, data catalogs, and data mesh principles.
              • Experience supporting AI/ML model pipelines, including feature stores and training set lineage.
              • Background in managing large-scale historical data backfills, data remediation workflows, or schema refactoring in production.
              • Understanding of regulatory compliance frameworks (HIPAA, GDPR, CCPA) as they relate to data governance.What Success Looks Like
                • All business-critical data pipelines are documented, version-controlled, observable, and traceable.
                • Schema changes are safe, validated, and governed across environments and teams.
                • Data flows and structures enable confidence scoring, downstream analytics, and ML inference without loss of provenance or integrity.
                • The business's data corpus becomes a first-class system of record - authoritative, explainable, extensible.Why Bitewell?We're not just building another app - we're creating technology that could fundamentally change how people eat and live.Our culture values boldness, intellectual curiosity, and a hands-on approach. We're looking for someone who can bring their authentic self to work, engage in thought-provoking discussions, and contribute to our mission with both expertise and enthusiasm.Ready to help us make "FoodHealth Score" a household term? Apply now to join our team and make an impact on one of the most important health challenges of our time.Additional DetailsLocation: San FranciscoCompensation: $150K - $160K with flexibility based on your experience and qualifications. Total compensation package includes equity & bonus and full benefits package.Bitewell celebrates diversity and is committed to building an inclusive environment for all. We're an equal opportunity employer and don't discriminate on the basis of race, color, ethnicity, religion, sex, gender identity, sexual orientation, age, disability status, or any other protected characteristic. We encourage candidates from all communities to apply and bring their authentic selves to our team as we work together to revolutionize how people make food choices.
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Keywords: Bitewell, San Francisco , Data Architect, Other , San Francisco, California