Senior Manager, Data Engineering

Purpose of the role

Join us to build a world-class data and analytics platform that will reshape automotive retail. You’ll lead the engineering discipline that powers our data lake, warehouse, real-time clickstream, and applied AI-turning large-scale data into trusted, high-impact products our customers use every day

What you’ll lead:

Data Platform Engineering Team - Own our AWS-based datalake, warehouse and core data infrastructure, including security, reliability, cost efficiency and scalability.

Analytics Engineering Team - Drive data modelling, transformation and pipeline standards through the lake/warehouse to power governed, reusable semantic layers and metrics.

Clickstream Team - Operate and evolve our real-time event ingestion and processing to bring product telemetry and digital signals into the platform.

Key outcomes & responsibilities:

• Run the function day-to-day. Plan, prioritise and deliver across the teams and ensure resilient operations
• Set platform direction. Support Data Architects and contribute to the modern data architecture on AWS across storage, compute, streaming, governance and cataloguing; align designs to the AWS Well-Architected Framework and the Data Analytics Lens.
• Raise engineering standards through Embed IaC, CI/CD for data, AI based development practices, MLOps, testing, observability, lineage and cost/FinOps; codify patterns for batch, streaming and ML.
• Deliver trustworthy data. Support the teams to establish modelling conventions (e.g., layer boundaries, naming, contracts), data quality SLAs, and a governed metrics layer consumable by our ThoughtSpot visualisation platform.
• Security, privacy & compliance. Champion least-privilege access, encryption, auditability and privacy-by-design across all datasets.
• People & performance. Lead managers and senior ICs; grow capability through coaching, clear career paths, hiring, and a high-performance, inclusive culture.
• Stakeholder leadership. Partner with Product, Platform, External 3rd Parties and Customer teams to convert business goals into a data roadmap, measurable outcomes and transparent delivery.

What you’ll bring:

• Proven leadership of multi-team data engineering organisations (platform, analytics engineering, streaming and ML/AI) in a product-led, cloud-native environment.
• Data Architecture and operational expertise with AWS analytics services and modern data architecture (lake + warehouse + streaming under unified governance).

• Strong track record shipping reliable, cost-efficient pipelines at scale; credibility in SQL/Python and with at least one of dbt/Spark.

• Proven experience using AI development tools to increase engineering efficiency

• MLOps experience: feature pipelines, automated testing, model versioning/registry, promotion workflows and post-production monitoring.
• Excellent people leadership: hiring, developing and performance-managing senior engineers; setting clear goals and creating psychological safety.
• Effective stakeholder management and communication-from architecture decisions to executive updates.
• Nice to have: experience with ThoughtSpot, automotive or adjacent domains.