Arbetsbeskrivning

Veritaz is a leading IT staffing solutions provider in Sweden, committed to advancing individual careers and aiding employers in securing the perfect talent fit. With a proven track record of successful partnerships with top companies, we have rapidly grown our presence in the USA, Europe, and Sweden as a dependable and trusted resource within the IT industry.

Assignment Description:

We are looking for a Senior Data Engineer to join our dynamic team.

What you will work on:

• Design, build, and optimize end-to-end data pipelines integrating multiple data sources.
• Develop and maintain data models, ensuring data quality, scalability, and performance.
• Work with Databricks, Unity Catalog, Apache Spark, and Delta Lake to implement advanced data engineering solutions.
• Collaborate with data scientists, software engineers, and project managers to deliver robust data integration and analytical capabilities.
• Utilize Azure Data Factory and Azure Data Lake for data ingestion, transformation, and storage.
• Implement CI/CD pipelines, version control (Git), and DevOps practices for automation and deployment.
• Apply data engineering best practices to ensure governance, security, and efficiency.
• Monitor and optimize cloud usage to improve system performance and cost-effectiveness.
• Contribute to continuous improvement by sharing insights, mentoring peers, and refining development standards.

What you bring:

• Minimum of 5 years of experience in data engineering or software development.
• Strong proficiency in SQL and Python for data manipulation and automation.
• Hands-on experience with Databricks, Unity Catalog, Apache Spark, and Delta Lake.
• Proven track record in building and maintaining ETL/ELT pipelines across diverse data sources.
• Deep understanding of Azure cloud services, including Azure Data Lake and Azure Data Factory, along with cost management expertise.
• Experience implementing CI/CD pipelines, version control (Git), and DevOps methodologies.
• Familiarity with data warehousing, dimensional modeling, and data lakehouse architectures.
• Strong knowledge of data engineering best practices with the ability to advocate and apply them effectively.
• Excellent analytical, problem-solving, and communication skills.
• Ability to work independently while collaborating effectively in cross-functional teams.
• Experience with Power BI is considered a strong advantage.