Senior Manager, Data Engineering

Keyloop

. Lead the engineering discipline powering the data lake, warehouse, real-time clickstream and applied AI .

Posted 10/20/2026full-timeReading • United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AWS-based data architecture, including data lake and warehouse management, while ensuring operational resilience and cost efficiency. Proven leadership in multi-team environments, focusing on data engineering, AI development practices, and effective stakeholder communication.

Highest-signal resume keywords

AWS Data ArchitectureData Engineering LeadershipSQL and Python ProficiencyMLOps ExperienceAI Development Tools

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ModellingData TransformationPipeline StandardsReal-Time Event ProcessingInfrastructure as Code (IaC)Continuous Integration/Continuous Deployment (CI/CD)Feature PipelinesAutomated TestingModel VersioningCost/FinOps

Soft Skills

People LeadershipStakeholder ManagementEffective Communication

Tools & Technologies

ThoughtSpotDbtSpark

Industry Keywords

Cloud-Native EnvironmentAutomotive DomainData GovernancePrivacy-by-DesignAuditability

Tech Stack

Tools & technologies

AWSCloudPythonSparkSQL

About the role

Key responsibilities & impact

Lead the engineering discipline powering the data lake, warehouse, real-time clickstream and applied AI
Run the function day-to-day by planning, prioritising and delivering across teams
Ensure resilient operations
Own the AWS-based data lake, warehouse and core data infrastructure, including security, reliability, cost efficiency and scalability
Drive data modelling, transformation and pipeline standards and build governed semantic layers and metrics
Operate and evolve real-time event ingestion and processing
Support modern AWS data architecture across storage, compute, streaming, governance and cataloguing
Raise engineering standards through IaC, CI/CD for data, AI-based development practices, MLOps, testing, observability, lineage and cost/FinOps
Establish modelling conventions, data quality SLAs and a governed metrics layer for ThoughtSpot
Champion least-privilege access, encryption, auditability and privacy-by-design
Lead managers and senior individual contributors; coach, hire and develop teams
Partner with Product, Platform, external third parties and Customer teams to create a data roadmap and measurable outcomes

Requirements

What you’ll need

Proven leadership of multi-team data engineering organisations covering 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
Strong track record shipping reliable, cost-efficient pipelines at scale
Credibility in SQL and Python and with at least one of dbt or Spark
Proven experience using AI development tools to increase engineering efficiency
MLOps experience including feature pipelines, automated testing, model versioning/registry, promotion workflows and post-production monitoring
Excellent people leadership, including hiring, developing and performance-managing senior engineers
Effective stakeholder management and communication
Keyloop doesn’t require academic qualifications; selection is based on experience and potential
Nice to have: experience with ThoughtSpot, automotive or adjacent domains

Benefits

Comp & perks

Collaborate and learn from industry experts from all over the globe
Game-changing products and services
Training and support to try new things, adapt to quick changes and explore different paths
Career progression opportunities
Inclusive work environment and culture
Pay and benefits reflecting performance
Investment in professional development
Supportive and collaborative culture
AI tools and training to boost creativity and productivity