At a Glance
- Tasks: Lead a team to build a world-class data and analytics platform for automotive retail.
- Company: Join Keyloop, a leader in digital transformation for the automotive industry.
- Benefits: Competitive pay, inclusive culture, career growth opportunities, and no strict academic requirements.
- Why this job: Shape the future of automotive retail with cutting-edge technology and innovative solutions.
- Qualifications: Proven leadership in data engineering and expertise in AWS analytics services.
- Other info: Collaborate with global experts and enjoy a supportive, diverse work environment.
The predicted salary is between 72000 - 84000 ÂŁ per year.
Keyloop bridges the gap between dealers, manufacturers, technology suppliers and car buyers. We empower car dealers and manufacturers to fully embrace digital transformation 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.
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 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 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 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.
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.
Senior Manager, Data Engineering employer: Keyloop
Contact Detail:
Keyloop Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Manager, Data Engineering
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work at Keyloop or similar companies. A friendly chat can lead to insider info about the role and even a referral!
✨Tip Number 2
Prepare for the interview by diving deep into Keyloop's tech stack and recent projects. Show us you’re not just a fit for the role but also genuinely interested in what we do. Tailor your examples to highlight your experience with AWS and data engineering.
✨Tip Number 3
Practice your storytelling skills! When discussing your past experiences, frame them in a way that showcases your leadership and problem-solving abilities. We want to hear how you’ve tackled challenges and driven results in your previous roles.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows us you’re serious about joining the Keyloop team. Let’s make this happen!
We think you need these skills to ace Senior Manager, Data Engineering
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Manager, Data Engineering role. Highlight your experience with AWS, data architecture, and leadership in data engineering. We want to see how your skills align with what we’re looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why you’re passionate about data engineering and how you can contribute to our mission at Keyloop. Be genuine and let your personality come through.
Showcase Your Achievements: When detailing your experience, focus on specific achievements that demonstrate your impact in previous roles. Use metrics where possible to quantify your success—this helps us see the value you can bring to our team.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team at Keyloop!
How to prepare for a job interview at Keyloop
✨Know Your Tech Stack
Familiarise yourself with the specific technologies mentioned in the job description, like AWS services and data engineering tools. Be ready to discuss your experience with SQL, Python, dbt, and Spark, as well as how you've used them in past projects.
✨Showcase Leadership Skills
Prepare examples that highlight your leadership experience, especially in managing multi-team data engineering organisations. Think about how you've developed senior engineers and fostered a high-performance culture, as this role requires strong people management skills.
✨Understand Stakeholder Management
Be ready to talk about your experience in stakeholder management. Prepare to explain how you've converted business goals into actionable data roadmaps and how you communicate complex technical decisions to non-technical stakeholders.
✨Emphasise Problem-Solving Abilities
Think of specific challenges you've faced in data engineering and how you overcame them. Highlight your approach to ensuring data quality and reliability, as well as your experience with MLOps and CI/CD processes, which are crucial for this role.