Data Engineer
The Data Engineer is responsible for building and maintaining scalable, reliable, and high‑quality data pipelines and infrastructure that power data products and analytics across the organisation. The role focuses on ensuring data is accurate, timely, and consistently processed, particularly in environments involving high‑volume transactional and API‑driven systems.
Key Responsibilities
- Design, build, and maintain ETL/ELT pipelines.
- Ingest data from internal systems and external APIs.
- Develop scalable data processing workflows (batch and/or real‑time).
- Integrate data from various sources, including transactional flows.
- Handle complex data scenarios such as event sequencing, idempotency, duplicate handling, partial or delayed data.
- Ensure consistency between source systems and analytical datasets.
- Implement transformation logic aligned with architectural data models.
- Build and maintain structured data layers for analytics consumption.
- Collaborate closely with the Data Architect on model implementation.
- Implement data validation, monitoring, and alerting mechanisms.
- Identify and resolve data inconsistencies or failures.
- Ensure high levels of data accuracy and availability.
- Optimise pipelines for performance and cost‑efficiency.
- Support scaling of data infrastructure as volumes grow.
- Ensure low‑latency data availability where required.
- Work closely with Data Architect, Analysts, and Manager.
- Support Analysts by ensuring availability of curated datasets.
- Contribute to continuous improvement of data platform capabilities.
Required Skills & Experience
- 3–7+ years experience in data engineering, backend engineering, or similar roles.
- Strong programming skills (Python, SQL).
- Solid understanding of ETL/ELT processes and data pipeline design.
- Experience working with APIs and integrating distributed systems.
- Experience handling transactional or event‑based data.
- Strong understanding of data transformation techniques, data warehousing concepts, and data modelling fundamentals.
- Experience with data orchestration and workflow tools.
- Ability to build robust, fault‑tolerant systems.
- Strong problem‑solving skills with attention to detail and data accuracy.
- Experience in iGaming, fintech, or high‑volume transactional environments.
- Experience with event streaming technologies (Kafka).
- Familiarity with modern data stack tools (Snowflake, BigQuery, dbt, Airflow).
- Experience with real‑time or near real‑time data processing.
- Understanding of idempotent processing and event ordering.
- Exposure to CI/CD and infrastructure‑as‑code practices.
- Experience supporting analytics or BI teams.
- Reliability and uptime of data pipelines; data freshness and latency;
- Reduction in data errors and inconsistencies; performance and scalability of data processing.
- Availability of high‑quality, curated datasets for analysts.
Benefits & Perks
- Dynamic and team‑oriented work environment.
- Opportunities for personal growth and learning.
- Inclusive and supportive team where suggestions are welcome.
- 26 days paid holiday per year, plus local bank holidays.
- Competitive salary.
- €400 annual wellness allowance.
- Hybrid working.
- Risk benefits such as pension, life assurance (4x annual salary), private medical insurance.
- Team‑building opportunities, flexible core hours (10 am – 4 pm).
- Employee assistance programme, 24/7 support.
- Local discounts and more.
All applied talent will be treated with respect and considered for further opportunities.