Data Engineer building trusted data platforms for decision making at Lyrebird Health. Collaborating with teams to develop and maintain data pipelines and analytics - ready tables.
About the role
- Senior Data Engineer managing data platform strategy and analytics architecture at HALOS scaleup company. Owning design and implementation of analytical data platform.
Responsibilities
- Define and evolve HALOS’ data platform strategy, aligned with a globally distributed, microservice-oriented architecture.
- Evaluate, select, and implement a modern data stack.
- 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.
- 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.
- Ensure high availability, data quality, and observability across all data workflows.
- Partner closely with backend and platform engineering teams to advise on data modelling decisions.
- Act as a data architecture advisor, ensuring data is designed well at source even when owned by other teams.
- Design data pipelines and storage strategies with cost efficiency as a first-class concern.
- Establish strong data governance standards, ensuring compliance with GDPR and internal security policies.
Requirements
- 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.
Benefits
- 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
Job title
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