Senior Data Engineer (Contract) – Dublin
Hybrid \| 3 days onsite in Dublin
This role offers the opportunity to shape robust cloud-native data pipelines, apply Snowflake at scale, and take ownership of automated testing and data quality engineering in a highly impactful environment.
Data Engineering \& Architecture
Design and build scalable, Snowflake-centric data pipelines supported by Spark, Hadoop, NiFi, and related technologies.
Develop high-performance data models and workflows tailored to large, regulated financial datasets.
Produce clean, maintainable Python and SQL code aligned with top-tier engineering standards.
Integrate governance frameworks, metadata, and lineage tracking into all solutions.
Data Quality \& Test Automation
Create and maintain automated validation frameworks for ETL/ELT processes.
Implement data quality checks, reconciliation routines, regression testing, and schema validation.
Execute unit, integration, and end-to-end testing across new and existing pipelines.
Utilize dbt testing, Python scripts, and custom utilities to support automated validation.
Collaboration \& Agile Delivery
Work closely with engineering, product, and data science teams to ensure quality is embedded throughout development.
Contribute to agile ceremonies, helping shape priorities around stability, performance, and delivery.
Assist in production support by analyzing data issues and performing rapid root-cause investigations.
Continuous Improvement \& Technical Leadership
Stay current on advances in Snowflake, data engineering tooling, and testing automation.
Share knowledge, mentor teammates, and champion engineering best practices.
Influence improvements across CI/CD, observability, and data reliability processes.
Experience
Core Technical Expertise
4+ years hands-on Snowflake experience
(performance tuning, modeling, advanced SQL).
7+ years as a Data Engineer
working with distributed, large-scale data platforms.
Strong background with Spark, Hadoop, Databricks, Kafka, and cloud-native data ecosystems.
Proficiency in Python for pipeline development and automation work.
Familiarity with orchestration and workflow management tools.
Testing \& Quality Engineering
Proven experience building and implementing testing strategies for ETL/ELT pipelines.
Knowledge of data profiling, anomaly detection, and statistical validation.
Experience integrating automated tests into CI/CD workflows.