Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Data Engineer Lead - NatGas and Power

Gunvor Group
London
1 month ago
Create job alert

Data Engineer Lead - NatGas and Power page is loaded

Data Engineer Lead - NatGas and PowerApply locations London posted on Posted 12 Days Ago job requisition id JR102268

Job Title:

Data Engineer Lead - NatGas and Power

Contract Type:

Time Type:

Job Description:

Reporting to the Head of Data, the Data Engineering Lead will oversee the design, development, and maintenance of high-performance data systems that support trading, risk, and analytics functions across the Natural Gas and Power business. This role bridges technical execution and business impact, ensuring that data pipelines, platforms, and products are robust, scalable, and aligned with enterprise data strategy.

The ideal candidate will lead a team of data engineers, collaborate with trading desks and analysts, and ensure that data infrastructure supports pre-trade modeling, live execution, and post-trade analytics with precision and reliability.

Main Responsibilities

1. Data Platform Ownership

  • Lead the development and maintenance of scalable data pipelines and databases tailored to Natural Gas and Power trading workflows.

  • Ensure seamless integration of internal and external data sources (e.g., market prices, fundamentals, grid data, weather feeds) into centralized platforms.

  • Deliver real-time, high-quality data to support trading decisions, risk management, and performance tracking.

2. Technical Leadership & Team Management

  • Manage and mentor a team of data engineers, fostering technical excellence and continuous learning.

  • Oversee code quality, architecture decisions, and deployment practices across the team.

  • Collaborate with the Global Head of Data to align engineering efforts with strategic priorities.

  • Lifecycle Management: Overseeing data enrichment, update, and deletion processes, and ensuring documentation in enterprise catalogs

3. Business Collaboration

  • Work closely with traders, quantitative analysts, and risk managers to understand data requirements and deliver fit-for-purpose solutions.

  • Translate business needs into technical specifications and ensure timely delivery of data products.

4. Data Quality & Governance

  • Implement monitoring systems to ensure data accuracy, completeness, and timeliness.

  • Support data governance initiatives, including metadata management, lineage tracking, and access controls.

  • Ensure compliance with regulatory standards (e.g., REMIT, EMIR) and internal audit requirements.

5. Innovation & Continuous Improvement

  • Evaluate and adopt new technologies (e.g., streaming platforms, time-series databases, ML pipelines) to enhance data capabilities.

  • Drive automation and optimization of data workflows to improve performance and reduce operational risk.

  • Contribute to the evolution of enterprise data architecture in collaboration with IT and analytics teams.

Profile

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field.

  • +10 years of experience in data engineering, with at least 2 years in a leadership or senior technical role.

  • Proven experience in energy trading environments, particularly Natural Gas and Power markets.

  • Expert in Python and SQL; strong experience with data engineering libraries (e.g., Pandas, PySpark, Dask).

  • Deep knowledge of ETL/ELT frameworks and orchestration tools (e.g., Airflow, Azure Data Factory, Dagster).

  • Proficient in cloud platforms (preferably Azure) and services such as Data Lake, Synapse, Event Hubs, and Functions.

  • Authoring reports and dashboards with either open source or commercial products (e.g. PowerBI , Plot.ly, matplotlib)

  • Programming

    • OOP

    • DevOps

    • Application development lifecycle

  • Web technologies

    • HTTP/S

    • HTML/Javascript

    • REST APIs

    • Authentication protocols

    • Data formats (CSV, JSON, XML, Parquet)

  • Experience with time-series databases (e.g., InfluxDB, kdb+, TimescaleDB) and real-time data processing.

  • Familiarity with distributed computing and data warehousing technologies (e.g., Spark, Snowflake, Delta Lake).

  • Strong understanding of data governance, master data management, and data quality frameworks.

  • Excellent communication and stakeholder management skills.

  • Ability to mentor junior engineers and foster a collaborative team culture.

  • Fluent in English; any other language an asset

If you think the open position you see is right for you, we encourage you to apply!


Our people make all the difference in our success.

Similar Jobs (1)European Power and Gas Quantitative Developerlocations 2 Locations posted on Posted 30+ Days Ago

At Gunvor, we are always looking for talented and motivated new people who will contribute to the success and growth of our company. Every day, with their know-how, expertise and passion, our people make the difference and enable us to achieve our vision. Our global business offers a wide variety of opportunities and career paths. If you are unable to find any suitable vacancies, we recommend that you set up alerts to be notified when a position matching your criteria becomes available.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer Lead - NatGas and Power

Data Engineer

Senior Data Engineer

Specialist Data Engineer

Specialist Data Engineer

Data Engineer & Operations Lead- Leading Company!

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Pre-Employment Checks for Data Science Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in data science reflects the discipline's unique position at the intersection of statistical analysis, machine learning innovation, and strategic business intelligence. Data scientists often have privileged access to comprehensive datasets, proprietary algorithms, and business-critical insights that form the foundation of organisational strategy and competitive positioning. The data science industry operates within complex regulatory frameworks spanning GDPR, sector-specific data protection requirements, and emerging AI governance regulations. Data scientists must demonstrate not only technical competence in statistical modelling and machine learning but also deep understanding of research ethics, data privacy principles, and the societal implications of algorithmic decision-making. Modern data science roles frequently involve analysing personally identifiable information, financial data, healthcare records, and sensitive business intelligence across multiple jurisdictions and regulatory frameworks simultaneously. The combination of analytical privilege, predictive capabilities, and strategic influence makes thorough candidate verification essential for maintaining compliance, security, and public trust in data-driven insights and automated systems.

Why Now Is the Perfect Time to Launch Your Career in Data Science: The UK's Analytics Revolution

The United Kingdom stands at the forefront of a data science revolution that's reshaping how businesses make decisions, governments craft policies, and society tackles its greatest challenges. From the machine learning algorithms powering London's fintech innovation to the predictive models guiding Manchester's smart city initiatives, Britain's transformation into a data-driven economy has created an unprecedented demand for skilled data scientists that far outstrips the available talent. If you've been contemplating a career transition or seeking to position yourself at the cutting edge of the digital economy, data science represents one of the most intellectually stimulating, financially rewarding, and socially impactful career paths available today. The convergence of big data maturation, artificial intelligence mainstream adoption, business intelligence evolution, and cross-industry digital transformation has created the perfect conditions for data science career success.

Automate Your Data Science Jobs Search: Using ChatGPT, RSS & Alerts to Save Hours Each Week

Data science roles land daily across banks, product companies, consultancies, scaleups & the public sector—often buried in ATS portals or duplicated across boards. The fix: put discovery on rails with keyword-rich alerts, RSS feeds & a reusable ChatGPT workflow that triages listings, ranks fit, & tailors your CV in minutes. This copy-paste playbook is for www.datascience-jobs.co.uk readers. It’s UK-centric, practical, & designed to save you hours each week. What You’ll Have Working In 30 Minutes A role & keyword map spanning Core DS, Applied/Research, Product/Decision Science, NLP/CV, Causal/Experimentation, Time Series/Forecasting, MLOps-adjacent & Analytics Engineering overlaps. Shareable Boolean searches for Google & job boards that strip out noise. Always-on alerts & RSS feeds that bring fresh UK roles to you. A ChatGPT “Data Science Job Scout” prompt that deduplicates, scores match & outputs ready-to-paste actions. A simple pipeline tracker so deadlines & follow-ups never slip.