The Role
Leads multi-team data engineering across AWS data lakes, warehouses, analytics engineering, streaming, and ML platforms. Owns platform strategy, reliability, security, governance, cost efficiency, data quality, MLOps, and engineering standards. Manages managers and senior individual contributors, develops talent, establishes delivery priorities, and partners with product, platform, customer, and external teams to deliver trusted data products and measurable business outcomes.
Summary Generated by Built In
Keyloop bridges the gap between dealers, manufacturers, technology suppliers and car buyers.
We empower car dealers and manufacturers to fully embrace digital transformation. How? By creating innovative technology that makes selling cars better for our customers, and buying and owning cars better for theirs.
We use cutting-edge technology to link our clients’ systems, departments and sites. We provide an open technology platform that’s shaping the industry for the future. We use data to help clients become more efficient, increase profitability and give more customers an amazing experience. Want to be part of it?
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.
Why join us?
We’re on a journey to become market leaders in our space – and with that comes some incredible opportunities. Collaborate and learn from industry experts from all over the globe. Work with game-changing products and services. Get the training and support you need to try new things, adapt to quick changes and explore different paths. Join Keyloop and progress your career, your way.
An inclusive environment to thrive
We’re committed to fostering an inclusive work environment. One that respects all dimensions of diversity. We promote an inclusive culture within our business, and we celebrate different employees and lifestyles – not just on key days, but every day.
Be rewarded for your efforts
We believe people should be paid based on their performance so our pay and benefits reflect this and are designed to attract the very best talent. We encourage everyone in our organisation to explore opportunities which enable them to grow their career through investment in their development but equally by working in a culture which fosters support and unbridled collaboration.
Keyloop doesn’t require academic qualifications for this position. We select based on experience and potential, not credentials.
We are also an equal opportunity employer committed to building a diverse and inclusive workforce. We value diversity and encourage candidates of all backgrounds to apply.
"At Keyloop, AI is a daily ally: We encourage and train every employee to use our AI tools to boost their creativity and productivity."
Skills Required
- Proven leadership of multi-team data engineering organizations spanning platform, analytics engineering, streaming, and ML/AI
- Experience in a product-led, cloud-native environment
- Data architecture and operational expertise with AWS analytics services
- Experience with modern data architecture combining data lakes, warehouses, streaming, and unified governance
- Track record of shipping reliable, cost-efficient pipelines at scale
- Credibility with SQL and Python
- Experience with at least one of dbt or Spark
- Experience using AI development tools to improve engineering efficiency
- MLOps experience including feature pipelines, automated testing, model versioning or registries, promotion workflows, and post-production monitoring
- People leadership experience hiring, developing, and performance-managing senior engineers
- Strong stakeholder management and communication skills
- Experience with ThoughtSpot
- Automotive or adjacent industry experience
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The Company
What We Do
As the largest global automotive technology company, Keyloop delivers cutting-edge solutions, tailored to the modern needs of auto retailers and OEMs alike. With 40 years of automotive DNA, and a deep understanding of what it takes to drive success, Keyloop solutions are delivered in over 90 countries, and trusted by more 20,000 retailers and 80 OEMs worldwide. From the showroom to the workshop, and everything in between, its technology facilitates distinctive customer experiences between key systems, tools and departments. With modern consumers demanding increasingly high levels of service and responsiveness, Keyloop and their partners connect retailers and OEMs to consumers through every step of their journey. Keyloop delivers a proven technology ecosystem that redesigns the automotive retail experience to cultivate lasting loyalty and optimise margins through increased efficiency, elevated experiences, and unrivalled connected data. For more information, please visit www.keyloop.com
