(Senior) Data Engineer in Renewable Energies

Who we are:

Asset Ocean is a subsidiary of Encavis, one of the leading independent producers of electricity from renewable energy sources. We provide a central solution for the renewable energy sector to manage data from multiple solar and wind farms. Our mission is to improve data management and accelerate decision-making by providing high-quality data access and actionable business insights - helping Encavis scale its decentralized generation portfolio through intelligent data use.

What you can expect:

• Build Scalable Data Products: You design, develop, and operate cloud-native data products that transform complex renewable energy and business data into trusted information for analytics, automation, AI, and decision-making.
• Shape Enterprise Data Models: You design and evolve enterprise-wide data models using Data Vault 2.0, dimensional modeling, and modern architectural approaches that provide a scalable foundation for business growth.
• Engineer Large-Scale Time Series Solutions: You create robust solutions for high-volume time series data, integrating and harmonizing production, forecasting, weather, market, pricing, curtailment, and availability data across multiple sources.
• Leverage AI-Native Engineering Practices: You actively use AI-powered development tools and coding agents to accelerate development, testing, documentation, troubleshooting, and code reviews while maintaining high engineering standards.
• Drive End-to-End Ownership: You collaborate directly with business stakeholders, translate business challenges into scalable solutions, and take responsibility from concept and design through production deployment and ongoing operations.
• Advance Engineering Excellence: You ensure reliability, observability, performance, data quality, and cost efficiency while contributing to architecture decisions, mentoring colleagues, and establishing best practices within the Data & AI team.

Your profile:

• Data Engineering Expertise: You bring at least five years of professional Data Engineering experience and have successfully designed, built, and operated enterprise-grade data platforms and analytical data products.
• Advanced Data Modeling Skills: You have deep expertise in enterprise data modeling, including Data Vault 2.0, dimensional modeling, and normalized data structures, and understand how to apply the right approach for different business needs.
• Modern Data Stack Experience: You have strong hands-on experience with Snowflake, dbt, advanced SQL, cloud-native ELT architectures, CI/CD pipelines, automated testing, lineage, monitoring, and Git-based engineering workflows.
• Time Series Engineering Know-how: You have experience processing large-scale time series data and understand concepts such as aggregation, interpolation, historization, resampling, and data quality management in analytical environments.
• AI-Native Engineering Mindset: You are experienced in working with AI-powered development tools and coding agents, understand both their potential and limitations, and can confidently validate and productionize AI-generated solutions.
• Business & Stakeholder Orientation: You enjoy working directly with business stakeholders, communicate technical concepts in a pragmatic way, challenge requirements constructively, and focus on delivering measurable business value.
• Communication & Stakeholder Management: You build trusted relationships across international business and technology teams and communicate fluently in English. German language skills are considered a plus.

What we offer:

Does that sound good?

Then we look forward to getting to know you!