Senior Manager, Data Engineering

Keyloop UK Ltd; Reading; On-site; GBP 80,000 - 100,000; Full time

Job summary

A leading tech firm in Reading is seeking a seasoned leader to head their data platform engineering. This role will oversee the AWS data lake and warehouse, ensuring effective operations and engineering standards. The ideal candidate has experience in managing multi-team data engineering efforts, strong AWS knowledge, and a track record in MLOps. Join to impact the automotive retail sector and thrive in an inclusive working environment.

Benefits

Performance-based pay

Training and support for career growth

Qualifications

• Proven leadership of data engineering organizations in a cloud-native environment.
• Operational expertise with AWS analytics services and modern data architecture.
• Strong track record shipping reliable, cost-efficient pipelines.

Responsibilities

• Lead day-to-day function and ensure resilient operations.
• Support Data Architects with a modern data architecture on AWS.
• Champion least-privilege access and privacy by design across datasets.

Skills

Leadership of multi-team data engineering organizations

Data Architecture expertise with AWS

SQL/Python programming

MLOps experience

Effective stakeholder management

Tools

AWS (S3, Glue, Redshift)

SQL

Python

dbt

Airflow

Job description

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 improves selling and owning cars for customers. We use cutting‑edge technology to link our clients’ systems, departments and sites.

We provide an open technology platform shaping the industry for the future, using data to increase efficiency and profitability and deliver amazing experiences.

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 IaC, CI/CD for data, MLOps, testing, observability, lineage and cost/FinOps; codify patterns for batch, streaming and ML.
• Deliver trustworthy data. Support teams to establish modelling conventions, 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 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 and offer opportunities to collaborate with industry experts worldwide, work on game‑changing products, and grow your career with training and support.

An inclusive environment to thrive

We’re committed to fostering an inclusive work environment and celebrating diversity every day.

Be rewarded for your efforts

We believe people should be paid based on performance, and our pay and benefits reflect this, designed to attract the best talent.

Keyloop doesn’t require academic qualifications for this position.

We select based on experience and potential, not credentials.

Equal Opportunity Employer

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. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.