Power Factors
Climate Tech
SeniorDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer at Power Factors. Skills: Data engineering, ML/AI, Time-series modeling, Cloud data platforms. Design production ETL pipeline. Build production ETL pipeline”
Industry & Context.
Root cause analysis
What They're Looking For.
Must Have
5+ years experience, SQL proficiency, English communication skills
Nice to Have
Master's degree preferred, PhD preferred, GCP Professional Data Engineer, AWS Data Analytics, Databricks Certified, Dbt Certified
What You'll Do.
Design production ETL pipeline
Build production ETL pipeline
Own canonical signal schema
Implement automated data quality gates
Implement dataset versioning
Maintain backfill jobs
Own cold-start strategy
Own model-loading strategy
Instrument service with logs
Instrument service with metrics
Integrate forecasts into platform
Build shadow validation pipeline
Run live inference in parallel
Log predictions and actuals
Produce validation reports
Support pilot customer rollout
Enable product for customers
Own incoming data tickets
Own integration tickets
How You'll Work.
Team & Collaboration
Modern warehouse technologies; Pipeline orchestration tools; Global team operations
Communication Scope
Written communication; Verbal communication
Process & Methodology
Agile, Scrum
Full Job Description
About Power Factors Power Factors is accelerating the green energy transition by providing advanced analytics and AI insights to operators of renewable energy assets. Our SaaS platforms are used to manage over 250 GW of wind, solar, hydro, and energy storage projects globally. By driving down operational costs and increasing revenue, we are tackling one of the world's most important challenges: making renewable energy the world's leading source of power. Our vision is to create a sustainable world powered by renewable energy. Our mission is to fight climate change with code. We are looking for a Senior Data Engineer to join the Innovation team as a core member of the PF-LLM programme — our initiative to build a from-scratch multivariate time-series foundation model across a fleet of ~1,000 wind and PV sites. You will be the connective tissue of the entire programme: owning the data foundation that makes state-of-the-art model training possible, the inference service that makes model outputs usable, and the platform integration that puts those outputs in front of pilot customers. From production ETL through to shadow-mode validation pipelines, you will be the engineer who keeps every track moving. This role is critical-path from day one. The Role — What You'll Do Data Foundation Design and build the production ETL pipeline from source systems to warehouse and feature store at fleet scale, covering thousands of wind and PV sites across multiple OEMs. Own canonical signal schema design across wind and PV asset classes and OEMs — the deepest technical unknown in the programme and the foundation everything else depends on. Implement automated data quality gates: sparsity and missingness checks, flatline detection, outlier flagging, and freshness validation, with alerting that generates tickets automatically. Implement dataset versioning sufficient to reproduce every trained model from scratch. Build and maintain backfill jobs, idempotency guarantees, and retry logic that
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