Data engineer in energy

EPEX SPOT; Amsterdam; Remote; EUR 120.000 - 160.000; Vollzeit

Benefits dieser Stelle

Home office

Training budget

Career growth

Leadership program

Zusammenfassung

EPEX SPOT ищет лидера по данным для проектирования и эволюции облачной Data Platform на Google Cloud. Вы будете сочетать инженерное мастерство с техническим лидерством, помогая развивать масштабируемые, AI‑ready продукты для аналитики и операций.

Требуется 7+ лет в Data Engineering, глубокие знания GCP и опыт наставничества. Предлагаются гибкие условия, обучение и путь к росту внутри группы EEX.

Qualifikationen

• Опыт разработки и эксплуатации облачных data-платформ на GCP не менее 7 лет.
• Глубокие знания BigQuery, Dataplex, Dataflow и Data Lake/Lakehouse на GCP.
• Опыт архитектурного проектирования, руководства и обучения инженеров.
• Умение работать в Agile и сотрудничать с Data Scientists и стейкхолдерами.
• Навыки IaC (Terraform), CI/CD, мониторинга и безопасности.

Aufgaben

• Проектирование и развёртывание масштабируемых data-пайплайнов и продуктов.
• Разработка пакетной и стриминговой обработки данных, обеспечение reliability и cost‑efficiency.
• Поддержка архитектурных решений и дорожной карты платформы.
• Модерирование код‑ревью и наставничество младших инженеров.
• Сопровождение внедрения Vertex AI и интеграции ML‑потоков.

Kenntnisse

GCP (облака)

Python

SQL

Data Engineering

DevOps

Agile

Ausbildung

Бакалавр/Магистр в CS/IT

Tools

BigQuery

Dataform

Dataplex

Cloud Storage

BigLake

Cloud Composer

Cloud Workflows

IAM/Security

Dataflow

Terraform

CI/CD

Git/Version Control

Jobbeschreibung

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.