Software Developer & Data Engineer

Build the food intelligence layer at WISEcode.

Most people have no real way to know what's in their food or what it does to them. The information is scattered, inconsistent, and written to sell rather than to inform. WISEcode exists to change that: to give people a source they can actually trust, and the freedom to decide for themselves once they have it.

Getting there takes more than a better app. It takes a system underneath that turns fragmented food data into answers that hold up: consistent, explainable, and the same whether they reach a parent scanning a label, a brand seeking verification, or an institution making decisions at scale. That system is what we are building, and it is the reason the work compounds instead of resetting with every new product.

The Role: We are hiring a

Software Developer & Engineer to work as a senior individual contributor, serving as the second engineer on The Pantry, our new data lakehouse (DuckLake on S3 Parquet, Postgres catalog, Prefect orchestration, Python throughout)

. You will work alongside our Data team, combining hands-on implementation with platform and data architecture design in an early-stage environment where the shape of the work is still yours to define.

You bring

3+ years of experience in a similar role, along with real comfort with ambiguity and pace. What you get in return is a problem that matters and the room to shape how it gets solved.

Key Responsibilities: Lakehouse Architecture & Implementation:

• Own end-to-end implementation and collaborate on data/platform architecture alongside our data team.
• 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 our engineering 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.
• Technical Skills: 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

Minimum Qualifications: 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.
• Preferred Qualifications: 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.
• Compensation: Competitive base, bonus, and meaningful equity. Details shared in the hiring process.