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Lead / Senior Data Engineer

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Onsite

Lead / Senior Data Engineer

Diggibyte Technologies

Lead / Senior Data Engineer

Skills

Google Cloud PlatformSQL QueriesData EngineeringPythonDatabricksGitAIAWSdbtPySparkAzure

14 days ago

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Important information


Contract type:

Permanent

Location:

Stockholm, Sweden

Work mode:

Onsite

Published on:

12 October 2026

What they need


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

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