Data Engineer

Job Description

What You Will Do?​

The Data Engineering Lead/Specialist will design, build, and maintain the robust data infrastructure primarily utilizing the Databricks Lakehouse Platform to support the Data Science and MarTech operations. This role is responsible for ensuring data is reliable, high-quality, and efficiently flows from source systems (CRM, MAP, CDP, web logs) into the Lakehouse architecture for analysis, modeling, and real-time activation.

Key Responsibilities

• Lakehouse Architecture: Design, implement, and optimize the data architecture within Databricks, leveraging Delta Lake for reliability and performance across the data ingestion and consumption layers.
• Data Pipeline Development: Design and implement scalable ETL/ELT data pipelines (batch and streaming) using tools like Databricks notebooks (PySpark/Scala) and related cloud orchestration services (e.g., Azure Data Factory, AWS Glue/Step Functions) to ingest, transform, and load high-volume marketing data.
• Databricks Optimization: Tune and optimize Databricks clusters and jobs for cost-efficiency and performance, specifically supporting high-volume MarTech data processing and large-scale ML model training (in collaboration with Data Science).
• MarTech Integration: Own the technical integration and data flow between core MarTech systems (CDP, CRM, Marketing Automation) and the central Lakehouse platform, ensuring data is ready for activation.
• Data Quality & Governance: Establish and enforce data quality checks, monitoring, and lineage practices within the Databricks environment to ensure data accuracy, consistency, and compliance.

Required Skills & Qualifications

• Extensive experience in data engineering, software engineering, or a related field.
• Bachelor´s degree Systems Engineering, Computer Engineering or Mathematics.
• Expert proficiency in SQL and the use of Py Spark or Scala for building complex data pipelines.
• Mandatory hands-on expertise with the Databricks Lakehouse Platform, including Delta Lake.
• Strong experience with cloud data platforms (AWS, Azure, or GCP) and their associated services for data storage and orchestration.
• Proven experience with modern data pipeline tools (e.g., Airflow, dbt) and data modeling techniques.

Work Properly.

• Hybrid: This position requires to work 3 days on site 2 days at home remote on a full-time basis.

In case you need any reasonable adjustment to continue with your process, let your recruiter know.

Remember to attach your CV when applying to this vacancy.

GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need gm immigration sponsorship now or in the future.

This role is categorized as hybrid. This means the selected candidate is expected to report to a specific location at least 3 times a week {or other frequency dictated by their manager}.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us 

We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Non-Discrimination and Equal Employment Opportunities

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

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