Data Engineer

Rhythm is a renewable energy and technology company that combines energy market expertise with technology, design, and data science to create products that help people manage their budgets and environmental footprint.

• Build and maintain scalable data pipelines using Python, SQL, and Spark-based frameworks such as Databricks;
• Ensure data pipeline reliability and performance at scale;
• Manage the full data lifecycle, including ingestion, transformation, modeling, and downstream analytics and BI use cases;
• Partner with Finance, Operations, Marketing, and Product stakeholders to understand data needs and deliver solutions that support business decisions;
• Own projects end-to-end, from problem definition and data exploration through implementation, deployment, and iteration;
• Improve the performance and scalability of distributed data systems by optimizing pipelines and transformations;
• Help define and evolve data models that support multiple business use cases;
• Collaborate with engineers through code reviews, shared ownership, and system design discussions;
• Contribute to a transparent engineering culture by surfacing problems early and solving them collaboratively.

• 3–6+ Years of experience in Data Engineering or similar roles, with hands-on ownership of production data pipelines;
• Strong experience with Python and SQL;
• Experience working with large datasets in distributed environments such as Spark, Databricks, or similar;
• Solid understanding of data modeling and transformation best practices;
• Experience working in cloud-based environments and familiarity with cloud data concepts;
• Ability to work cross-functionally and communicate effectively with technical and non-technical stakeholders;
• Ability to operate independently without close supervision in a fast-paced environment;
• Nice to have: Experience with Databricks and Delta Lake, familiarity with AWS and cloud-based data architectures, exposure to BI tools and analytics delivery, experience with operational, financial, or customer lifecycle data, interest in machine learning or advanced analytics.

• Flexible work-life balance with a mix of remote work and office work;
• Professional development opportunities across technical and business domains;
• Opportunity to contribute to a sustainability-focused energy company.