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.
Senior Data Engineer at Keyrus leading the design, development, and delivery of scalable data platforms. Collaborating with teams to translate requirements into production - grade solutions and mentoring engineers.
Senior Data Engineer for global payments platform designing ETL pipelines and data models. Collaborating across teams to tackle complex data challenges in an innovative fintech environment.
Data Warehouse Modelling Engineer designing and maintaining data models using Data Vault 2.0 for iGaming industry. Collaborating with stakeholders and optimizing data models in a hybrid work environment.
Senior Data Engineer driving impactful data solutions for the climate logistics startup HIVED's core data platform. Collaborating with cross - functional squads to enhance analytics and delivery.
Data Engineer developing and maintaining CRE forecasting infrastructure for Cushman & Wakefield. Collaborates with senior economists and technical teams to ensure high - quality data solutions.
Data Engineer at PwC, engaging with Azure cloud services to enhance data handling and integrity. Responsibilities include pipeline optimizations, documentation, and collaboration with stakeholders.