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The Senior Data Engineering Lead drives the design and the standards definition to ensure robust data pipelines and data products across EDP's ecosystem. You'll set engineering standards, automate workflows, and ensure that EDP's data is always trusted, timely, and ready for analytics and AI.
Job Responsibility:
Design, develop, and maintain patterns for scalable data pipelines and integration frameworks
Lead implementation of data engineering best practices, templates, and reusable components
Collaborate with architects and domain teams to support the delivery of production-grade data products
Ensure best practices for data quality, monitoring, and observability across platforms
Promote automation and CI/CD adoption within data teams
Optimize cost and performance across hybrid cloud environments
Mentor engineers and contribute to EDP's data engineering community of practice
Requirements:
Degree, Master's, or Doctorate in engineering or related field
6+ years in data engineering or platform development
Hands-on experience with Python, SQL, Spark, and ETL/ELT orchestration tools (Airflow, dbt, Data Factory)
Deep knowledge of Databricks, Fabric, Snowflake, and other Azure, AWS and GCP data solutions
Experience in CI/CD, IaC, GitOps, and cloud infrastructure
Familiarity with data quality frameworks, metadata management, and observability tools
Strong collaboration, problem-solving, and technical leadership skills
Nice to have:
Experience with real-time data streaming (Kafka/Event Hub), data mesh, or ML Ops
Certifications such as Azure Data Engineer or Databricks Data Engineer
What we offer:
Empower our employees through a positive and innovative work environment that promotes collaboration and agile decision-making
Respect and value each person, providing a flexible, healthy, and inclusive workplace with a range of attractive benefits
Provide a meaningful work experience and prepare our people for future challenges through different opportunities for development and internal mobility
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