Senior Data Engineer at innovative asset management provider designing data infrastructure for the energy sector. Collaborating with teams to enable machine learning and optimize renewable resources.
Responsibilities
Design, develop, and optimize data infrastructure for reliable ingestion and processing of large-scale time-series data.
Collaborate with cross-functional teams and communicate results effectively.
Enable advanced machine learning and data-driven decisions for renewable energy optimization worldwide.
Requirements
**Data Architecture & Strategy:** Lead the design and implementation of robust data architectures and pipelines that support real-time and batch processing of wind and solar datasets.
**Data Integration & Transformation:** Oversee the ingestion and harmonization of diverse data sources, ensuring reliability, consistency, and performance.
**ETL & Orchestration:** Build, maintain, and optimize ETL/ELT processes with a focus on scalability, modularity, and reusability.
**Database Engineering:** Design and manage high-performance data warehouses and time-series databases (e.g., TimescaleDB, PostgreSQL, MySQL).
**Quality & Governance:** Implement automated data validation, quality checks, and monitoring systems to ensure integrity across the data lifecycle.
**DevOps Collaboration:** Contribute to CI/CD processes and containerization (e.g., Docker) to support robust and agile data delivery.
**API Integration:** Develop and maintain interfaces for seamless data access and integration with internal and external systems.
**Cross-Functional Collaboration:** Partner with product, analytics, and machine learning teams to understand business needs and translate them into data solutions.
**Documentation & Knowledge Sharing: **Promote best practices through comprehensive documentation and mentorship of junior engineers.
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