Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy - fast. We're combining first-principles thinking with cutting-edge technology to build a radically better energy system. We raised $170M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group and strategic angels like Nico Rosberg, the Co-Founder of Solana and GPs behind Meta, Revolut, Spotify, Uber and more.

We’re creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations. By selling directly to consumers, we cut out the middleman, lower costs and pass on savings to customers.

But we’re not stopping there. We’re also building the Energy Network: a decentralised platform of smart devices that rewards users in Energy Dollars for electrifying their homes, shifting usage to off-peak hours, and helping balance the grid. This network strengthens grid stability - a critical foundation for scaling AI data centers and other energy-intensive industries.

Responsibilities

• Build and maintain scalable, reliable data pipelines to support analytics, reporting, and product needs
• Own the design and evolution of analytical schemas, translating business logic into structured, intuitive data models
• Migrate and transform data from Postgres into Clickhouse, ensuring performance and reliability
• Develop and maintain DBT models that reflect our business domain and make data easily accessible for teams
• Implement tests and data quality checks to ensure reliable and trustworthy datasets
• Identify and eliminate duplicates, improve data consistency, and enforce clean modeling standards

Requirements

• 3+ years of experience as a Backend Engineer or in a data-focused engineering role
• Proficiency in Python and SQL, with the ability to write clean, efficient code and queries
• Hands-on experience working with relational databases, particularly Postgres
• Experience designing schemas and building data models that reflect real-world business logic
• Familiarity with DBT or similar data transformation frameworks
• Strong understanding of data validation, testing, and quality assurance practices

Bonus

• Familiarity with cloud-based data infrastructure or data orchestration tools
• Experience with CI/CD practices for data pipelines and transformations

Benefits

• Competitive salary and an equity sign-on bonus
• Biannual bonus scheme
• Fully expensed tech to match your needs
• Paid annual leave
• Breakfast and dinner allowance for office based employees

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We're creating a fully integrated energy company: from developing solar, wind and hydrogen projects to real-time power trading and distributed energy installations. By selling directly to consumers, we cut out the middleman, lower costs and pass on savings to customers.

Responsibilities

You will build and maintain scalable, reliable data pipelines to support analytics, reporting, and product needs. This includes owning the design and evolution of analytical schemas, translating business logic into structured, intuitive data models. You will also migrate and transform data from Postgres into Clickhouse, ensuring performance and reliability.

You will develop and maintain DBT models that reflect our business domain and make data easily accessible for teams. Additionally, you will implement tests and data quality checks to ensure reliable and trustworthy datasets. You will identify and eliminate duplicates, improve data consistency, and enforce clean modeling standards.

Requirements

• 3+ years of experience as a Backend Engineer or in a data-focused engineering role
• Proficiency in Python and SQL, with the ability to write clean, efficient code and queries
• Hands-on experience working with relational databases, particularly Postgres
• Experience designing schemas and building data models that reflect real-world business logic
• Familiarity with DBT or similar data transformation frameworks
• Strong understanding of data validation, testing, and quality assurance practices

Bonus

• Familiarity with cloud-based data infrastructure or data orchestration tools
• Experience with CI/CD practices for data pipelines and transformations

Benefits

• Competitive salary and an equity sign-on bonus
• Biannual bonus scheme
• Fully expensed tech to match your needs
• Paid annual leave
• Breakfast and dinner allowance for office-based employees

XML job scraping automation by YubHub

At Valvoline Global Operations, we're proud to be The Original Motor Oil, but we've never rested on being first. Founded in 1866, we introduced the world's first branded motor oil, staking our claim as a pioneer in the automotive and industrial solutions industry.

Job Purpose

We are seeking a highly skilled and motivated Data Engineer to join our growing data and analytics team. The ideal candidate will have strong experience designing and developing scalable data pipelines, integrating complex systems, and optimizing data workflows. Proficiency in Databricks and SAP Datasphere is preferred, as these platforms are central to our data ecosystem.

How You Make an Impact (Job Accountabilities)

• Design, build, and maintain robust, scalable, and high-performance data pipelines using Databricks and SAP Datasphere.
• Collaborate with data architects, analysts, data scientists, and business stakeholders to gather requirements and deliver data solutions aligned with stakeholders' goals.
• Integrate diverse data sources (e.g., SAP, APIs, flat files, cloud storage) into the enterprise data platforms
• Ensure high standards of data quality and implement data governance practices. Stay current with emerging trends and technologies in cloud computing, big data, and data engineering.
• Provide ongoing support for the platform, troubleshoot any issues that arise, and ensure high availability and reliability of data infrastructure.
• Create documentation for the platform infrastructure and processes, and train other team members or users in platform effectively.

What You Bring to the Role (Job Qualifications / Education / Skills / Requirements / Capabilities)

• Bachelor's or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• 5-7+ years of experience in a data engineering or related role.
• Strong knowledge of data engineering principles, data warehousing concepts, and modern data architecture.
• Proficiency in SQL and at least one programming language (e.g., Python, Scala).
• Experience with cloud platforms (e.g., Azure, AWS, or GCP), particularly in data services.
• Familiarity with data orchestration tools (e.g., PySpark, Airflow, Azure Data Factory) and CI/CD pipelines.

Competencies Desired

• Hands-on experience with Databricks (including Spark/PySpark, Delta Lake, MLflow, Unity Catalog, etc.).
• Practical experience working with SAP Datasphere (or SAP Data Warehouse Cloud) in data modeling and data integration scenarios.
• SAP BW or SAP HANA experience is a plus.
• Experience with BI tools like Power BI or Tableau.
• Understanding of data governance frameworks and data security best practices.
• Exposure to data lakehouse architecture and real-time streaming data pipelines.
• Certifications in Databricks, SAP, or cloud platforms are advantageous.

Working Conditions / Physical Requirements / Travel Requirements

• Normal Office environment.
• Prolonged periods of computer use and frequent participation in meetings
• Occasional walking, standing, and light lifting (up to 10 lbs)

• Minimal travel required.

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