Original listing text, shown exactly as published by the company.
About the Role
We are looking for a Senior Backend Engineer, Data Systems to help design and build the core data foundations of our platform.
This role is for an engineer who is deeply comfortable translating complex real-world concepts into clean relational data models, durable SQL schemas, clear data contracts, and maintainable backend services. You will work at the intersection of backend engineering, data architecture, and domain modeling.
A major focus of this position will be building systems where business rules and operational logic can be expressed through data structures and database-backed rules, rather than being hardcoded exclusively in application logic. You will help shape how we represent entities, relationships, constraints, validation rules, ingested data, and derived logic across the product.
This is not a traditional analytics or BI data engineering role. It is a product/backend engineering role with a strong data systems focus.
What You’ll Do
- Design and evolve relational data models that represent complex domain concepts, entities, relationships, and workflows.
- Build and maintain SQL schemas, constraints, indexes, migrations, and query patterns that support scalable backend systems.
- Define and enforce data contracts between services, APIs, ingestion pipelines, and downstream consumers.
- Develop ingestion and normalization workflows for structured, semi-structured, and external source data.
- Move business logic from ad hoc application code into well-modeled, extensible data structures, including:
- configurable rules
- eligibility or feasibility checks
- mappings and lookup tables
- domain-specific constraints
- decision logic represented in data
- Partner with product, domain experts, and engineers to convert ambiguous or evolving requirements into clear data abstractions.
- Build backend services and APIs that expose, validate, and operate on these data models.
- Improve the consistency, traceability, and maintainability of data across the system.
- Help establish patterns for:
- versioned data models
- schema governance
- data validation
- audit-ability
- backward-compatible contracts
- Participate in architecture discussions and code reviews, especially where data modeling decisions have long-term consequences.
Required Qualifications
- Strong professional experience as a backend software engineer working on production systems.
- Deep experience with relational databases, especially PostgreSQL or similar systems.
- Strong ability to design:
- normalized schemas
- associative/relationship tables
- constraints and validation logic
- enum / lookup models
- lifecycle-aware data structures
- Strong SQL skills, including:
- complex joins
- aggregation
- CTEs
- views or materialized views where appropriate
- query performance awareness
- Experience defining or working with data contracts between services, APIs, and persistence layers.
- Experience building or maintaining data ingestion, transformation, or normalization workflows.
- Ability to reason carefully about business rules, edge cases, and how domain logic should be represented in software.
- Strong programming ability in Python.
- Experience working with ORMs and migration frameworks such as:
- SQLAlchemy
- Alembic
- or comparable tools
- Strong communication skills and comfort collaborating with engineers, product stakeholders, and domain experts.
Preferred Qualifications
- Experience designing rule-driven systems, policy engines, feasibility checks, or configuration-driven business logic.
- Experience deciding when logic belongs in:
- application code
- SQL/database structures
- rules tables
- services or domain layers
- Experience modeling complex operational domains such as:
- simulations
- logistics
- planning systems
- geospatial systems
- defense, aerospace, or other highly structured data environments
- Experience with:
- PostGIS or geospatial data
- event-driven systems
- versioned datasets or snapshots
- data lineage / provenance
- imported external datasets with inconsistent or incomplete source quality
- Familiarity with API schema design and typed contracts, such as:
- Pydantic
- JSON Schema
- protobuf or similar tools
- OpenAPI
