Senior Data Engineer
Billee Technologies, Inc. · Dallas, TX · 2 mo ago
RemoteRemoteEducationFull-time
Skill Requirements
- Python
- SQL
- Dimensional Modeling
- Dagster
- DuckDB or MotherDuck
- Azure
- Hex
- MCP
Responsibilities
- Contribute to the modeled data and pipelines behind customer-facing reports on consumption, cost, and rate trends.
- Ingestion, semantic models, storage solutions, and retrieval (SQL, RAG, vector, or graph-based).
- Own testing, lineage, freshness monitoring, and alerting so data issues are caught before a customer sees them.
- Translate vague product and compliance questions into concrete models, working directly with engineers, analysts, and PMs.
- Warehouse: MotherDuck / DuckDB
- Orchestration: Dagster
- Transformation: DBT
Requirements
- 4+ years in data platform engineering. Bonus if you've been a primary builder on a platform from early stages.
- Comfort analyzing data directly.
- Experience with AI/LLM-adjacent data work: RAG pipelines, embedding stores, evaluation frameworks (e.g. LangSmith or PydanticAI), or knowledge-graph approaches for structured retrieval.
- Azure experience
- Utility, energy, PropTech, or billing domain background
- No-task-too-small mindset. Small team, lots of surface area. You'll occasionally build a quick report or debug someone else's pipeline.
Qualifications
- Strong Python and SQL.
- Direct experience with our stack is a significant plus. In order of preference:
- Dagster (asset-based orchestration, sensors, partitions) — strongly preferred over Airflow experience alone
- DuckDB or MotherDuck — even side-project or exploratory use
- Comfortable with ambiguity. Our roadmap shifts; you can prioritize and make progress on incomplete information.
- Ownership mindset. You treat the platform as a product — monitoring and proactive thinking about future needs
- Quality advocate. You believe tests, observability, and lineage are features, not overhead.
- Curious about new tooling. You've been watching the modern data stack evolve and have opinions — about DuckDB, about Dagster vs. Airflow, about where LLMs do and don't belong in data pipelines.