Senior Data Specialist

Alex Staff Agency

21h•Remote

About The Position

We are seeking a Senior Data Specialist with a deep understanding of data and proficiency in Python for data wrangling. This role is not for a platform engineer or a pure pipeline builder, but for a data specialist comfortable with research, investigation, and the essential work of making messy energy market data usable. The position involves significant tasks such as mapping BM units to power plants and fuel types, reconciling legacy data formats, ensuring consistency between different Elexon message types, and cleaning time-series data. This requires genuine investigation, cross-referencing sources, making judgment calls, and documenting edge cases, as there is no readily available API to solve these problems. Python, particularly Pandas and Numpy, will be the primary tool to minimize manual effort, but comfort with investigative work is essential. The ideal candidate finds satisfaction in understanding a dataset's structure and quirks rather than just processing data superficially.

Requirements

Strong Python skills for data work, fluent with pandas, comfortable writing clean, testable code, and capable of building reusable data processing logic.
Solid SQL skills, including complex queries, window functions, and CTEs in PostgreSQL.
Experience with messy, real-world data, including reconciliation, cleaning, or mapping work where full automation is not always possible.
Methodical and detail-oriented approach, with an ability to notice inconsistencies and understand root causes.
Good documentation habits, understanding the importance of documenting mappings and assumptions.
Self-directed, able to own ambiguous problems, conduct independent research, and communicate findings clearly.

Nice To Haves

Experience with energy, utilities, or market data (any geography).
Familiarity with UK energy markets, Elexon data, or grid operations.
dbt experience for transformation pipelines.
Exposure to time-series data challenges (irregular timestamps, gaps, restatements).

Responsibilities

Map BM units from Elexon to their corresponding power plants, substations, and fuel types, combining API data, public registers, and manual research.
Map substations to ETYS zones and grid supply points.
Build and maintain reference/master datasets that link identifiers across disparate sources (Elexon, National Grid ESO, TEC register, etc.).
Document mappings, assumptions, and known limitations clearly for downstream users.
Reconcile legacy data formats with current formats (e.g., historical operational data stored in different schemas or granularities).
Ensure consistency between different Elexon message types, understanding the market data structure to handle discrepancies and align data like BOALF, BOD, and DISBSAD.
Investigate discrepancies between data sources and determine authoritative values.
Clean time-series data, including detecting outliers (price spikes, meter errors), filling gaps appropriately, and resolving overlapping or duplicate timestamps.
Develop reusable Python-based cleaning routines applicable across datasets.
Understand the root causes of data quality issues (settlement reruns, late submissions, format changes).
Write and maintain Python data grabbers for energy market APIs.
Build dbt models to transform raw data into clean, analysis-ready datasets.
Orchestrate workflows via GitHub Actions.
Design PostgreSQL schemas that reflect an understanding of the domain.