Lead the development of scalable data pipelines for AI systems, ensure data quality, and collaborate across teams to drive innovation.
About Ministry Brands:
Ministry Brands is a leading provider of SaaS operational management systems, payments platforms, digital engagement tools, and background screening solutions for faith-based, non-profit, and for-profit organizations. We serve more than 95,000 customers as a trusted partner in digital transformation and enablement—advancing missions, driving efficiencies, and building engaged communities for more than four decades.
The diverse and real-world experiences of our team members serving their communities make us stronger together and enhance our ability to advance digital transformation for the greater good.
Ministry Brands is committed to acknowledging and valuing our employees’ differences and to creating an environment in which every individual’s unique strengths and abilities are developed and celebrated. We welcome everyone and are dedicated to fostering a culture where all employees have equal opportunities to be heard and to reach their full potential.
About the role:
Are you a hands-on data engineer who thrives in a fast-paced, feedback-driven environment? We’re looking for a Senior Data Engineer - AI to help shape the future of Ministry Brands’ next generation of AI-powered products.
You’ll lead the design and development of scalable, secure, and high-performance data pipelines and infrastructure, directly supporting production-ready AI and agentic systems. This role offers the opportunity to work closely with cross-functional teams to bring innovation to life—while actively contributing to a dynamic R&D-driven culture based in Galway.
Our engineering team embraces Agile and Extreme Programming principles. We value collaboration, continuous feedback, and ownership at every level.
What you'll do:
- Develop, deploy, and maintain high-performance microservices that consume and produce data, applying data-driven monitoring and iteration to continually improve service efficiency and impact.
- Ensure data quality, reliability, and optimal performance across platforms.
- Implement strategies to mitigate data bias and ensure model fairness.
- Collaborate across teams to drive innovation through high-quality data solutions.
- Embed security, compliance, and best practices into all aspects of data infrastructure.
What you bring:
- Proven experience in building production-level data infrastructure for AI/agent-based systems.
- Expertise in:
- Azure Fabric, Azure Data Factory, Azure Synapse Analytics
- Data Lake Storage, Databricks, Apache Spark, ClickHouse
- Python
- Strong foundation in ETL/ELT best practices and modern data architecture.
- Familiarity with:
- AI/ML evaluation metrics and benchmarking techniques
- A/B testing methodologies
- Bias mitigation strategies and model fairness assessments
Preferred experience:
- Experience leading data engineering teams or initiatives in AI-focused environments.
- Ability to mentor peers and lead by example.
- A strong collaborative spirit and a drive for continuous learning and improvement.
What's in it for you:
- Private Health Insurance: 100% employer-paid (Irish Life Health – 4D Health 2 Plan) for employees and eligible dependents.
- Dental Cover: Employer-paid Level 1 dental coverage through DeCare; optional upgrades available.
- Vision Care: Access to eye care and eyewear via DeCare (employee-paid).
- Life Insurance: 4x salary lump sum life assurance plus value of pension fund.
- Income Protection: 66.67% of base salary after a 26-week waiting period.
- Pension Scheme: Employer match of 5% in year 1, 6% after year 3; fully vested after 2 years.
- Employee Assistance Programme (EAP): Confidential 24/7 counselling and wellbeing support for employees and family.
- Annual Leave: 25 days paid time off per year (pro-rated in year 1).
- Maternity Leave: Up to 26 weeks at 100% salary after 1 year of service.
- Bike to Work Scheme: Tax-free bike/e-bike purchase up to €1,250/€1,500, repaid via payroll deductions.
Top Skills
Spark
Azure Data Factory
Azure Fabric
Azure Synapse Analytics
Clickhouse
Data Lake Storage
Databricks
Python
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