Data engineer in energy trading
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
- Agile
- AI
- Analytics
- API
- BigQuery
- CI/CD
- Cloud
- Cloud Native
- Data Engineering
- Data Lake
- Data Lineage
- Data Pipelines
- Data Quality
- DevOps
- ELT
- ETL
- Event Driven Architecture
- GCP
- Git
- IAM
- Infrastructure as Code
- Lakehouse
- Machine Learning
- Metadata Management
- Observability
- Python
- SQL
- Terraform
- Version Control
- Vertex AI