Data and ML Engineer (Remote)

Cyrantos is partnering with a fast-growing energy technology company building large-scale battery installations and an intelligent network managing electricity in real time to make renewables reliable and dispatchable. The client is in an early-stage environment building the data platform from scratch for real-time and historical energy data.

• 3-6 years of experience in data or ML engineering or applied data science with production deployment experience
• Fluent in writing clean, tested, production-grade Python code
• Hands-on experience with ETL/ELT pipelines, data modeling, and time-series data handling
• Strong skills with PostgreSQL, including schema design and query tuning
• Treat data quality, validation, and monitoring as integral to engineering
• Comfortable working directly with AWS infrastructure without abstractions
• Experience running models and pipelines in production as APIs, batch jobs, or scheduled workflows
• Ability to work pragmatically and make decisions with imperfect information in an early-stage environment

Nice to have:

• Exposure to energy markets, industrial systems, or hardware-adjacent data such as sensor streams and EMS integrations

• Take end-to-end ownership of data pipelines ingesting high-volume time-series feeds and deliver clean, validated, reliable data downstream
• Build data quality by default with validation, anomaly detection, and monitoring embedded in pipelines
• Shape the evolving data platform architecture balancing real-time and historical processing
• Collaborate with data scientists to productionize forecasting and optimization models and maintain live systems
• Improve modeling and algorithm quality through code reviews and technical contribution
• Embed data and models directly into the core product alongside engineering teams
• Manage data relationships and integrations with external partners such as EMS providers and trading partners

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