Databricks Engineer, Data Platform & Data Science Tooling

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What we offer:

At Magna, you can expect an engaging and dynamic environment where you can help to develop industry-leading automotive technologies. We invest in our employees, providing them with the support and resources they need to succeed. As a member of our global team, you can expect exciting, varied responsibilities as well as a wide range of development prospects. Because we believe that your career path should be as unique as you are.

Group Summary:

Magna is more than one of the world’s largest suppliers in the automotive space. We are a mobility technology company built to innovate, with a global, entrepreneurial-minded team. With 65+ years of expertise, our ecosystem of interconnected products combined with our complete vehicle expertise uniquely positions us to advance mobility in an expanded transportation landscape.

Job Responsibilities:

Job Responsibilities – Must Have

Non-negotiable skill: 3+ years hands-on: PySpark, Delta Lake, Workflows, Unity Catalog, Databricks

Design, develop, and implement efficient and reliable data pipelines using Databricks Delta Live Tables.

Develop pipelines for structured and unstructured data (i.e. documents, JSON, Parquet, Excel) supporting AI and ML consumption downstream.

Implement and extend data models (i.e. fact/dimension tables, domain data marts) following designs defined by the Senior DE and AI team.

Write clean, modular, reusable PySpark and SQL transformation logic that is testable, documented, and deployable via CI/CD

Write and optimize complex SQL queries using Databricks SQL for data extraction, transformation, and loading.

Implement and manage data governance and metadata using Databricks Unity Catalog to ensure data quality and discoverability.

Collaborate with data scientists, analysts, and other engineers to understand data requirements and deliver appropriate data solutions.

Monitor, troubleshoot, and optimize existing data pipelines and data infrastructure.

Stay up-to-date with the latest trends and technologies in data engineering and the Databricks ecosystem.

Contribute to the semantic layer that powers Power BI dashboards.

Orchestration and Data Ops- Should Have

Build and manage Databricks Workflows: configuring task dependencies, retry policies, and failure alerting

Monitor & manage workspaces as Workspace admins.

Follow and contribute to CI/CD practices: version control, pull requests, automated testing, and deployment to Dev/QA/Prod environments using Azure DevOps or GitHub Actions.

Understanding of infrastructure as a service, Terraform and willingness to learn terraform for automation at infrastructure level.

Package and deploy reusable logic as Python libraries following team standards

Monitor pipeline health, investigate failures, and resolve data issues within SLA

FinOps Awareness – Should Have

Write cost-conscious PySpark avoiding unnecessary full scans, optimizing joins, using appropriate cluster types

Apply Delta table best practices (i.e. VACUUM, OPTIMIZE, compaction) to manage storage costs

Follow cluster policies defined by platform leads and flag unusual resource consumption

Experience/QUALIFICATIONS

4-6+ years of overall data engineering experience

2+ years of hands-on Azure Databricks experience in production environments

Demonstrated ability to build and deliver pipelines - not just maintain or support them

Experience working within a defined architecture and contributing to its improvement

Comfortable working with multiple data source types - relational, file-based, API

Awareness, Unity, Empowerment:

AI-Assisted Screening Disclosure

As part of our commitment to a fair, consistent, and efficient recruitment process, we may use artificial intelligence (AI) tools to assist in the initial screening of applications submitted through our Workday system. These tools help identify qualifications and experience that align with the role requirements. Please note that AI is used solely to support our recruiters. Final decisions are always made by the hiring manager and the hiring team. Importantly, no applicant data is shared externally through these AI tools. All information remains securely within our systems and is handled in accordance with our privacy and data protection policies.

Under conditions defined by applicable law, you may have the right to request an explanation of how AI is used to support decision-making.

If you have any questions or concerns about this process, feel free to contact our Talent Attraction team.

Worker Type:

Regular / Permanent

Group:

Magna Corporate