
Data Engineering Expert
5 days ago
About Hedin IT AB
Hedin IT AB is a leading mobility enabler in Europe, seeking a Senior Data Engineer to join our Business Intelligence team. We are committed to delivering innovative solutions that drive business growth and customer satisfaction.
The Role
As a Senior Data Engineer, you will design, build, and maintain a scalable data platform that supports enterprise-wide analytics and decision-making. You will develop and optimize data pipelines, integrations, and models to ensure accurate, accessible, and structured data for business insights.
Main Responsibilities
- Data Pipeline Development: Design and develop scalable data pipelines for efficient extraction, transformation, and loading (ETL/ELT) of large-scale datasets.
- Lakehouse Architecture: Architect and enhance our lakehouse architecture using Databricks, ensuring flexibility, scalability, and performance.
- Data Quality and Governance: Ensure data quality, governance, and security by implementing best practices for monitoring, validation, and compliance.
- Optimization and Automation: Optimize data performance and cost-efficiency by tuning queries, storage, and compute resources for enterprise-scale workloads. Standardize and automate data integration across multiple internal and external sources, ensuring seamless interoperability.
Requirements
- A degree in Computer Science, Data Science, Software Engineering, or related field.
- Several years of experience in data engineering, working with large-scale data platforms in an enterprise setting.
- Strong SQL and Python skills, optimizing queries and processing large datasets.
- Hands-on experience with cloud-based platforms like Azure, Databricks, or similar.
- Deep knowledge of ETL/ELT processes using Apache Airflow, dbt, or Azure Data Factory.
- Understanding of lakehouse architectures, including Delta Lake and Medallion principles.
- Experience in data modeling, performance tuning, and data governance for reliability and scalability.
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