Data Engineering Manager

About the Role

As part of the AI & Data organization, the Enterprise Business Intelligence (EBI) team is central to NXP’s data analytics success. We provide and maintain scalable data solutions, platforms, and methodologies that empower business users to create self-service analytics and drive data-informed decisions.

We are seeking a Data Engineering Manager to lead a team of skilled Data Engineers. In this role, you will be responsible for overseeing the design, development, and maintenance of robust data pipelines and data models across multiple data platforms, including Databricks, Teradata, Postgres and others. You will collaborate closely with Product Owners, Architects, Data Scientists, and cross-functional stakeholders to ensure high-quality, secure, and scalable data solutions.

Key Responsibilities

• Lead, mentor, and grow a team of Data Engineers, fostering a culture of innovation, collaboration, and continuous improvement.
• Oversee the design, development, and optimization of ETL/ELT pipelines and data workflows across multiple cloud and on-premise environments.
• Ensure data solutions align with enterprise architecture standards, including performance, scalability, security, privacy, and compliance.
• Collaborate with stakeholders to translate business requirements into technical specifications and data models.
• Drive adoption of best practices in data engineering, including code quality, testing, version control, and CI/CD.
• Partner with the Operational Support team to troubleshoot and resolve data issues and incidents.
• Stay current with emerging technologies and trends in data engineering and analytics.

Required Skills & Qualifications

• Proven experience as a Data Engineer with at least 12+ years in ETL/ELT design and development.
• 5+ years of experience in a technical leadership or management role, with a track record of building and leading high-performing teams.
• Strong hands-on experience with cloud platforms (AWS, Azure) and their data services (e.g., S3, Redshift, Glue, Azure Data Factory, Synapse).
• Proficiency in SQL, Python, and PySpark for data transformation and processing.
• Experience with data orchestration tools and CI/CD pipelines (GitHub Actions, GitLab CI).
• Familiarity with data modeling, data warehousing, and data lake architectures.
• Understanding of data governance, security, and compliance frameworks (e.g., GDPR, HIPAA).
• Excellent communication and stakeholder management skills.

Preferred Skills & Qualifications

• Experience with Agile methodologies and DevOps practices.
• Proficiency with Databricks, Teradata, Postgres, Fivetran HVR and DBT.
• Knowledge of AI/ML workflows and integration with data pipelines.
• Experience with monitoring and observability tools.
• Familiarity with data cataloging and metadata management tools (e.g., Alation, Collibra).

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