Data & BI Engineer – Commodity Markets Analytics, CTRM Platform

Job not on LinkedIn

🕒 5 days ago

🇦🇪 United Arab Emirates (UAE) – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Business Intelligence Developer

👻 Ghost score 17%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Raw Ventures

WebsiteLinkedInAll Job Openings

11 - 50 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

<Raw Ventures> Raw Ventures is a venture studio and investment firm that backs and builds startups across MediaTech, HealthTech, biotech, and sustainability sectors using evergreen capital, hands-on advisory, and talent development. It operates an ecosystem combining investment (Evergreen), AI-powered advisory (Raw Advisory), and creative/talent support (Raw Creative) to help technologies move from proven concepts to practical impact, and it focuses on innovative content, healthcare and biotech ventures. The firm emphasizes building interconnected companies rather than isolated startups and publishes news about its portfolio and activity.

📋 Description

• Own the data and BI layer of the CTRM platform end to end • Build ingestion pipelines from internal systems and external market data providers, including scheduling, retries, backfills and vendor schema changes • Model commodity data covering prices and curves, cargoes and flows, deals, positions, costs, units, calendars, pricing periods and reference data • Build dashboards and reports for price analysis, spreads, cargo flows and margin, including crack spread monitoring, cargo tracking, refinery margin analysis and storage economics • Implement data quality, lineage and reconciliation, including freshness checks, price-series gap detection, duplicate-cargo detection and trusted-source reconciliation • Establish agreed definitions across trading, operations and finance and document reproducible calculations • Translate trader requirements into working analytics and iterate with end users • Evaluate and recommend new data sources, tools and integrations as the platform grows • Work directly with traders, operations, commercial staff, the senior data scientist and founders

🎯 Requirements

• 4+ years as a Data Engineer, BI Developer, Analytics Engineer or in a comparable role, with ownership of production pipelines and reporting • Strong SQL • Python for pipelines, automation and analysis, including pandas and SQLAlchemy or similar • Practical data modelling experience, including dimensional modelling, star schemas, and dbt or equivalent • Hands-on experience with a BI tool such as Power BI, Tableau, Metabase or Superset, from requirements through to a relied-upon dashboard • Commodity markets experience, ideally crude oil and refined products; knowledge of price assessments, forward curves, crack spreads and cargo nominations • Strong, demonstrable interest in commodity markets may partly compensate for experience; zero exposure will not • Experience working seriously with coding agents and strong verification habits, including row-count and freshness checks, reconciliation, and transformation tests • Comfortable working directly with traders and commercial staff and explaining data issues in their terms • English sufficient to present work and defend design decisions • Professional proficiency in Russian • Nice to have: market data provider and API experience with Kpler, Platts, OPIS, Argus or Bloomberg • Nice to have: cloud data warehouses such as Snowflake, BigQuery or Databricks • Nice to have: workflow orchestration with Airflow, Prefect, Dagster or similar • Nice to have: experience in an energy trading company, commodity house or data-heavy financial environment, including CTRM/ETRM exposure

🏖️ Benefits

• Ownership of the data and BI layer, and room to shape the architecture and tooling • Direct access to experienced commodity traders, the founders and decision-makers; short feedback loops • Licences and access to leading market data platforms, including Kpler, Platts and OPIS • Generous AI tooling budget — frontier models are a working expense, not a perk • Competitive compensation, discussed individually