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Senior Data Engineer

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    Company Details Confidential
  • Image for Job Ref
    Ref: #JOB-2424291
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    Co. Dublin,
  • Image Position
    No of positions: 1
  • Image Part Time
    Paid Position
  • Image Hours per week
    40 hours per week
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    Negotiable
  • Image for Published
    Published On: 10 Dec 2025
  • Image for Closing
    Closing On: 07 Jan 2026

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Overview
 
Are you passionate about building scalable data solutions and ensuring data integrity in high-impact financial technology? Do you thrive in solving complex data challenges while maintaining rigorous quality standards?
Join the team behind Crypto Secure, a cutting-edge risk assessment platform helping banks gain visibility into crypto spend, transaction volumes, and AML risk exposure. Working with modern technologies like Snowflake, Hadoop, Spark, NiFi, and cloud-native architectures, you’ll play a dual role: designing robust data pipelines and implementing comprehensive testing strategies to guarantee reliability and trust.
 
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Role Responsibilities
Data Engineering & Platform Development
•	Design, build, and maintain scalable data pipelines using Snowflake, Hadoop, Spark, NiFi, and related big data technologies.
•	Implement data architectures and optimize workflows for massive financial datasets.
•	Write high-quality, maintainable code in Python and SQL following best practices.
•	Integrate data governance principles, metadata management, and lineage tracking into solutions.
Data Quality Assurance & Testing
•	Develop automated testing frameworks and validation scripts for ETL processes and data transformations.
•	Implement data quality checks, reconciliation processes, and regression testing suites to ensure accuracy, completeness, and timeliness.
•	Perform unit, integration, and end-to-end testing for data pipelines and schema changes.
•	Use tools like dbt tests, custom Python utilities for automated validation.
Collaboration & Agile Delivery
•	Work closely with Data Engineers, Product, and Data Science teams to embed testing into the development lifecycle.
•	Participate in agile ceremonies (sprint planning, backlog refinement, retrospectives) with a focus on quality and delivery.
•	Support production incident response with rapid data validation and root cause analysis.
Continuous Improvement
•	Stay current with emerging data engineering and testing technologies.
•	Contribute to team knowledge sharing, mentoring junior engineers, and improving technical standards.
•	Shape best practices for data reliability, testing automation, and CI/CD integration.
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Skills & Qualifications
Core Technical Expertise
•	Advanced SQL and experience with relational and NoSQL databases.
•	Strong experience with Snowflake, Hadoop, Spark, Databricks, Kafka, and cloud data platforms.
•	Proficiency in Python for both data engineering and test automation.
•	Familiarity with orchestration tools and workflow management systems.
Testing & Quality
•	Proven experience in data testing methodologies, ETL validation, and automated testing frameworks.
•	Knowledge of data profiling, anomaly detection, and statistical validation techniques.
•	Experience integrating testing into CI/CD pipelines.
Professional Attributes
•	Strong problem-solving and analytical skills with attention to detail.
  • This vacancy is suitable for Remote/Blended working
  • Sector:

Career Level

  • Experienced [Non-Managerial]

Candidate Requirements

Essential Desirable

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