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Epex Spot

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Data engineer in energy trading

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Summary

Lead Data Engineer who designs, builds, and evolves EPEX SPOT's cloud-native data platform on Google Cloud Platform — creating scalable batch and streaming pipelines and data products with BigQuery, Dataform, Dataplex, and Dataflow — while mentoring data engineers, enforcing governance, and enabling AI/ML use cases with Vertex AI.

Описание: As a Lead Data Engineer, you will play a pivotal role in designing, developing, and evolving EPEX SPOT's cloud-native Data Platform on Google Cloud Platform (GCP). You will combine hands-on engineering expertise with technical leadership, helping deliver trusted, scalable, and AI-ready data products that support business operations, analytics, and innovation initiatives.

Задачи:

  • Designing and implementing scalable data pipelines and data products
  • Building robust batch and streaming data processing solutions
  • Ensuring platform reliability, performance, security, and cost efficiency
  • Supporting architecture decisions and technical roadmap execution
  • Acting as the technical escalation point for complex engineering challenges
  • Coaching and mentoring Data Engineers in technical and professional growth
  • Conducting code reviews and design reviews
  • Encouraging knowledge sharing and continuous learning
  • Supporting onboarding and development of new team members
  • Driving adoption of engineering standards and best practices
  • Implementing governance capabilities using Google Dataplex
  • Supporting metadata management, lineage, cataloguing, and data quality initiatives
  • Ensuring compliance with security, privacy, and regulatory requirements
  • Enabling self-service analytics through reusable and governed data products
  • Promoting DevOps and DataOps practices
  • Supporting a culture of transparency, ownership, and continuous improvement
  • Building data foundations for analytics and AI use cases
  • Supporting the integration of Vertex AI and related AI services
  • Collaborating with Data Scientists to operationalize Machine Learning solutions

Требования:

  • Strong hands‑on experience with: BigQuery, Dataform, Dataplex (catalog, lineage, data quality, tag application), Data lake and Lakehouse implementation on GCP: Cloud Storage, external tables, BigLake, and the trade-offs between external and materialized data, Cloud Composer /Cloud Workflows, Cloud Run /Functions, IAM and Security Services, Cloud Monitoring and observability, Dataflow ELT/ETL architecture and implementation
  • API-based data integration
  • Data Contract implementation in the pipeline (assertions, quality checks, validation at build time)
  • Real-time and streaming architecture
  • Metadata management and data lineage
  • Data quality management
  • Event-driven architectures
  • AI-assisted engineering: proficient with GCP AI assistance (Gemini in BigQuery, Gemini Code Assist) and able to coach the data engineers on using it productively and safely
  • Python SQL
  • Infrastructure as Code (Terraform preferred)
  • CI/CD pipelines
  • Git and version control
  • DevOps and DataOps practices
  • Platform monitoring and observability
  • Performance optimization and cost management
  • Proven experience working in Agile environments
  • Strong technical leader who drives results through expertise, influence, and a passion for developing engineering talent.
  • Excellent communicator and collaborator, able to engage effectively with both technical and non-technical stakeholders in international environments.
  • Combines a proactive, analytical, and continuous improvement mindset with a strong sense of ownership, accountability, and a commitment to delivering high-quality business value.
  • Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, Data Engineering, or a related field.
  • Minimum 7 years of experience in Data Engineering, Software Engineering, or a related discipline.
  • Proven experience building and operating cloud-native data platforms.
  • Strong hands‑on experience with Google Cloud Platform data services.
  • Будет плюсом: Google Professional Data Engineer; Google Professional Cloud Architect; Google Professional Machine Learning Engineer; Terraform Associate

Условия:

  • We offer you the flexibility of working from home or other locations for the best possible work-life balance.
  • We invest in your continuous development with a dedicated annual training budget to enhance your skills through various upskilling programs and initiatives.
  • We support your career aspirations with clear pathways for advancement within the company and the EEX Group.
  • We offer and support the possibility to explore new roles within the company to expand your skills and experience.
  • We promote a culture of recognition and reward with the EPEX SPOT leadership journey that encourages everyone’s progression and development.

Skills

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