Software Developer & Data Engineer

• Lakehouse Architecture & Implementation: Own end-to-end implementation and collaborate on data/platform architecture alongside Nicholas.

• Source Ingestion: Build and establish patterns for a variety of sources including APIs, text from public sources, and external databases.

• Identity & Entity Resolution: Merge the many records we collect for each product, across retailers and dates, into one trustworthy published record. Decide which source wins on each disagreement, and keep every original record so each published value can be traced to its source.

• Pipeline Consolidation & Enrichment: Consolidate existing food enrichment pipelines down to a single pipeline in collaboration with Kevin's team.

• Downstream Connectors: Build robust connectors to feed collapsed food data to WISE Intel and the consumer app.

• Operational Discipline & Configuration: Maintain strict fail-fast config discipline (magic values in config files; early loud failures for missing settings).

• Data Quality & Reporting: Establish ingest capabilities and quality reporting for Data Assembly readiness.

• Technical Documentation: Write plain, short, dated decision records prior to code implementation.

• Languages: Native proficiency in Python and SQL.
• Storage & Query Engines: DuckDB, DuckLake, S3 Parquet.
• Databases: Postgres, DynamoDB (state management).
• Orchestration & Frameworks: Prefect, Kubernetes/Fargate job runners; familiarity with dbt, Dagster, or Airflow.
• AWS Infrastructure: S3, ECS, Lambda, EventBridge, SNS, Terraform, IAM.
• Reporting & Data Modeling: Lakehouse, analytic/dimension design; Quarto reporting; Medallion architecture (bronze/clean), star schema (food sighting, ingredient, nutrient, provenance).
• CI/CD: github actions

• 3+ years of experience in a similar role 

• Proven track record of designing and shipping a lakehouse or data warehouse from scratch, and operating it for at least one year in production.

• Demonstrated experience treating data identity and entity resolution as first-class architectural questions.

• Experience running batch data pipelines that invoke paid cloud/third-party APIs at scale with strict cost efficiency and budget controls.

• Experience pairing daily with other engineers in a fast-paced environment.

• Experience making architectural trade-offs between lightweight/embedded query engines (e.g., DuckDB) versus distributed systems (Spark, Databricks, Snowflake).

• Familiarity with data acquisition methods (e.g., web scraping, OCR API integration).

• Note: Food or nutrition domain knowledge, deep Spark/Databricks/Snowflake experience, and people management experience are explicitly NOT required for this role.

Competitive base, bonus, and meaningful equity. Details shared in the hiring process.

• Location: Fully remote 

• Unlimited PTO & Paid Holidays: Unlimited time off and 10 paid holidays

• Financial Wellness: 401(k) with a 4% company match, immediately vested

• Health Benefits: Comprehensive medical, dental, vision, life, and additional ancillary coverage. 

  • 100% coverage for employees, with 80% covered for dependents 

  • 100% employer paid STD, LTD, Identity Theft, and Life insurance 

  • FSA and HSA plans available, for our HSA:

    • $200/mo contributions for Employee plans

    • $400/mo contributions for Employee + Dependent plans

We are building the layer that food decisions will run on. That is quiet, compounding work: broadening coverage, sharpening precision, and making every output repeatable and defensible. We value transparency, rigor, and respect for the person making the decision, who deserves clear information and the freedom to reach their own conclusion. Come in early enough and you help shape how this system works instead of operating inside one someone else already designed.