Senior Manager, Data Engineering

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, 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.
• 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

Tech Stack (experience We Value)

Heavily AWS‑based (e.g., S3, Lake Formation, Glue, Athena/Redshift, EMR, Kinesis); transformation and modelling (SQL, dbt, Spark); orchestration (Airflow/Dagster/Prefect); languages (Python/SQL); CI/CD & IaC (GitHub/GitLab, CloudFormation); observability (CloudWatch + data quality/lineage tooling); ThoughtSpot as the visualisation layer; MLOps (SageMaker and/or MLflow Model Registry).

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 .

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.