Senior Data Engineer (Contract) – Dublin

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.