Senior Data Engineer - Platform & Analytics

• Essential

HALOS is an advanced body camera and cloud software scaleup, working with some of the biggest names in security, services, and law enforcement. At HALO, we're passionate about safety and innovation, constantly staying ahead of threats and reducing risk.

What sets HALOS apart is not just the cutting‑edge technology we develop but the culture we've nurtured. Our team embodies openness, transparency, and a "one team" spirit. We're a group of passionate individuals, all working on exciting and impactful projects. Here, you'll find an environment that fosters collaboration, creativity, and a shared sense of purpose.

We are seeking a Senior Data Engineer – Platform & Analytics to join HALOS as our first dedicated data hire. This is a foundational role with significant influence over how data is produced, shared, and consumed across the organisation.

You will own the design and implementation of our analytical data platform while playing an advisory role in how application data is modelled and exposed by our core product teams. This role sits at the intersection of analytics, data platform engineering, and application architecture.

While the role is highly hands‑on, it is suited to a senior individual contributor with the ambition and capability to grow into a future Head of Data role as the company scales.

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• Data Platform Architecture & Strategy
  
• Define and evolve HALOS’ data platform strategy, aligned with a globally distributed, microservice‑oriented architecture
  
• Evaluate, select, and implement a modern data stack. Our core infrastructure is AWS and our primary visualisation tool is Metabase, but you will have a key role in choosing our warehousing, orchestration, and transformation tooling
  
• Design a scalable data architecture capable of handling high‑volume IoT telemetry alongside transactional business data
  
• Support the long‑term evolution toward a data mesh–inspired approach, where domain teams own their data and the platform provides standards, tooling, and enablement
  
• Data Engineering & Pipelines
  
• Build and maintain robust, scalable data pipelines for ingesting structured and semi‑structured data from multiple sources
  
• Develop and manage high‑quality analytical data models (SQL / dbt) that serve as reliable, well‑documented sources of truth
  
• Support both batch and streaming use cases, selecting pragmatic solutions based on scale, latency, and cost
  
• Ensure high availability, data quality, and observability across all data workflows
  
• Advisory Role on Application Data
  
• Partner closely with backend and platform engineering teams to advise on data modelling decisions that impact analytics, reporting, and downstream systems
  
• Provide guidance on schema design, event structures, and data contracts to ensure application data is well‑structured, evolvable, and analytics‑friendly
  
• Help teams understand trade‑offs between transactional and analytical concerns without owning day‑to‑day OLTP development
  
• Act as a data architecture advisor, ensuring data is designed well at source even when owned by other teams
  
• Cost Optimisation & Global Scale
  
• Design data pipelines and storage strategies with cost efficiency as a first‑class concern, particularly in a high‑throughput IoT environment
  
• Continuously evaluate architectural trade‑offs across storage tiers, processing models, and regional deployments
  
• Help ensure the data platform scales globally without linear increases in cost or operational complexity
  
• Governance, Security & Enablement
  
• Establish strong data governance standards, ensuring compliance with GDPR, privacy regulations, and internal security policies
  
• Work with engineering and product teams to define best practices around data access, retention, and sensitivity
  
• Optimise and administer Metabase (or alternative) to ensure internal teams and customers have access to accurate, performant analytics
  
• Act as the technical data subject matter expert across the organisation
  

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• Essential
  
• 5+ years’ experience in data engineering or data platform roles
  
• Strong experience with AWS (e.g. S3, Lambda, IAM, Kinesis, Glue)
  
• Expert‑level SQL and strong Python skills for data processing and integration
  
• Hands‑on experience designing and operating modern data warehouses (e.g. Redshift, Snowflake, BigQuery)
  
• Experience with workflow orchestration tools such as Airflow, Dagster, or Prefect
  
• Proficiency with dbt (data build tool) and modern analytical modelling practices
  
• Experience supporting BI tools such as Metabase, Looker, or Tableau
  
• Highly Valued
  
• Experience working alongside microservice‑based application architectures
  
• Strong understanding of transactional vs analytical data modelling trade‑offs
  
• Experience influencing schema design or event contracts in collaboration with application teams
  
• Experience optimising data platforms for cost and scale
  
• Exposure to event‑driven or streaming architectures
  
• Nice to Have
  
• Experience working with IoT or high‑volume telemetry data
  
• Experience operating within an AI or ML‑enabled data ecosystem
  
• Infrastructure‑as‑Code experience (Terraform or CloudFormation)
  
• Experience in a high‑growth startup or scale‑up environment
  

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• Generous Annual Leave Allowance
  
• Competitive salary and commission/bonus package
  
• Learning and Development opportunities
  
• Private Health Insurance
  
• Cycle to work scheme
  
• Home & Tech scheme
  
• Regular company events and social initiatives
  

Here’s what we expect the hiring process for this role to be, should all go well with your candidacy. This entire process is expected to take 1‑3 weeks to complete and you’d be expected to start on a specific date.

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• 30 minute introductory meeting with the recruiting team
  
• 45 minute Interview with department hiring manager
  
• 30 minute meeting with wider department
  
• Offer!
  

We’re an Equal Opportunity Employer and embrace a diversity of backgrounds, cultures, and perspectives. We do not discriminate on the basis of race, colour, gender, sexual orientation, gender identity or expression, religion, disability, national origin, protected veteran status, age, or any other status protected by applicable national, federal, state, or local law.