Manager, Data Engineering

We're looking for a seasoned Data Engineering Manager to lead our team in designing, developing, and maintaining data pipelines that support our Data Hub strategy. As a key member of our Global Data Insight & Analytics team, you'll be responsible for building and maintaining data assets and services that empower Artificial Intelligence, Data Science, and Software Engineering.

Responsibilities:

• Lead a high-performing team of Portfolio Data Engineers, fostering a culture of collaboration, innovation, and continuous improvement.
• Strategically prioritize and manage team workloads, ensuring effective task allocation and resource capacity to support team goals.
• Provide expert technical guidance and mentorship, ensuring adherence to best practices, coding standards, and architectural guidelines.
• Act as the Chief Data Technical Anchor for the PLMA domain, resolving critical incidents through Root Cause Analysis (RCA) and implementing permanent, resilient architectural fixes.
• Oversee the design, development, maintenance, scalability, reliability, and performance of data platform pipelines, aligning them with business needs and strategic objectives.
• Contribute to the long-term strategic direction of the Data Platform by proactively identifying opportunities for best practice adoption and standardization.
• Champion data quality, governance, and security standards, ensuring compliance and safeguarding sensitive data assets.
• Enhance efficiency and reduce redundancy by consolidating common tasks across teams.
• Effectively communicate decisions to stakeholders, building strong relationships and ensuring alignment on data initiatives.
• Maintain awareness of industry trends and emerging technologies to inform technical decisions.
• Lead the implementation of customer requests into data assets, ensuring optimized design and code development.
• Guide the team in delivering scalable, robust data solutions and contribute hands-on to critical projects, including design and code reviews.
• Lead technical decisions that drive data innovation and resilience.
• Demonstrate full stack cloud data engineering expertise, covering automation, versioning, ingestion, integration, transformation, optimization, and data modeling.
• Engage in agile planning, including scope, work breakdown structure, as well as roadblock resolution.
• Design solutions for cost and consumption optimization, scalability, and performance.
• Collaborate with Data Architecture and stakeholders on solution design, data consolidation, retention, purpose of use, compliance, and audit requirements.
• Drive engineering excellence by establishing and monitoring SWE-centric quality metrics (including DORA metrics and P99 latency targets).

Requirements:

• Bachelor's degree in Computer Science, Information Technology, Information Systems, Data Analytics, or a related field.
• 8+ years of experience in complex data environments, demonstrating increased responsibilities and achievements with:

+ Expertise in programming languages such as Python or Scala, and strong SQL skills. + Experience with ETL/ELT processes, data warehousing, and data modeling. + Experience with CI/CD pipelines, Docker, Git/Gerrit, and experience designing resilient deployment strategies and sophisticated release management. + Familiarity of data governance, privacy, quality, and monitoring.

• Proven experience in implementing sophisticated testing strategies, driving quality tool adoption, establishing comprehensive code review processes, and setting observability standards with advanced monitoring and proactive alerting.
• 5+ years of experience within the automotive industry or related product development environments and product lifecycle management.
• 5+ years of experience in leading software or data engineering teams, with a focus on team development and project success.
• 5+ years of experience in Big Data environments or expertise with Big Data tools, including:

+ Data processing frameworks and data modeling. + In-depth knowledge and practical experience with Google Cloud Platform services. + Proven experience in monitoring and optimizing costs and compute resources in hyperscaler platforms.

• Significant experience leveraging Generative AI and LLMs to optimize data engineering workflows (e.g., automated code generation, documentation, or metadata management).

Preferred Qualifications:

• Master's degree in Computer Science, Engineering, or a related field.
• Expertise in GCP based data engineering services like BQ, Dataflow, Airflow, Dataform, Datastream, Apache Beam, Cloud Run, Cloud Functions
• Familiarity with automotive Product Development processes, including program planning, design validation, and cross-functional collaboration across engineering, manufacturing, and supplier teams to deliver data-driven insights at each lifecycle stage
• Experience in managing and scaling serverless applications and clusters, focusing on resource optimization and robust monitoring and logging strategies.
• Proficiency in unstructured data ingestion, including experience with data modeling and preparation techniques to support AI and machine learning workloads.
• Experience with AI architecture and AI enabling tech (graph database, vector database, etc)
• Familiarity with data visualization tools (e.g., Power BI, Tableau).
• Working knowledge of ontology, semantic modeling, and related technologies