Lead / Senior Data Engineer
# Lead / Senior Data Engineer **Diggibyte Technologies** · Stockholm · `On-site` 🕒 **Статус:** *Опубликовано: 3 дня назад* · *Источник: Indeed* --- ### About the Role Full Time Lead / Senior Data Engineer - Stockholm, Sweden - 4–12 Years - Onsite About the Role Diggibyte is looking for an experienced Lead / Senior Data Engineer to design, build, and optimize modern data platforms that power business intelligence, analytics, and AI-driven solutions. The ideal candidate will have strong expertise in cloud-based data engineering, scalable ETL/ELT pipelines, and the Databricks Lakehouse Platform. If you are passionate about solving complex data challenges and delivering high-performance solutions, we’d love to hear from you. Key Responsibilities - Lead the design, development, and maintenance of scalable data engineering solutions on the Databricks Lakehouse Platform . - Develop, optimize, and maintain high-performance data pipelines using Python and PySpark . - Build reliable data transformation workflows and analytical models using DBT . - Design scalable ETL/ELT pipelines to process structured and unstructured data efficiently. - Work extensively with Databricks, PySpark, and SQL to deliver robust data solutions. - Leverage cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform (GCP) for modern data architectures. - Implement data governance, metadata management, and security using Unity Catalog . - Collaborate with data scientists, analysts, architects, and business teams to understand data requirements. - Ensure data quality, performance optimization, and adherence to best engineering practices. - Mentor junior engineers and contribute to technical leadership within the team. Required Skills & Technologies - Databricks Lakehouse Platform - Python - PySpark - SQL - DBT (Data Build Tool) - AWS / Microsoft Azure / Google Cloud Platform - Unity Catalog - Data Warehousing & ETL/ELT - Data Modeling - Version Control (Git) Preferred Qualifications - Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Engineering, or a related field. - 4–12 years of professional experience in Data Engineering. - Strong understanding of cloud-native data platforms and distributed data processing. - Experience with performance tuning and optimization of large-scale data pipelines. - Excellent analytical, problem-solving, and communication skills. Good to Have - Databricks Certified Data Engineer Associate or Professional certification. - Experience with Databricks Auto Loader . - Knowledge of Delta Live Tables (DLT) or Lakeflow Declarative Pipelines . - Exposure to CI/CD practices for data engineering projects. - Familiarity with data governance and security best practices. Why Join Diggibyte? - Work on cutting-edge cloud and data engineering projects. - Collaborate with experienced technology professionals. - Opportunity to work with modern data platforms and AI-ready architectures. - Continuous learning and professional development. - Competitive salary and excellent career growth opportunities. - Flexible and collaborative work environment
Наблюдалась 2026-10-15, впервые 2026-10-12, источник — Indeed.