About the role

The Senior Data Engineer will own the department's data integration and analytics platform, managing the AWS data warehouse and ELT pipelines. They will also design AI-native data capabilities and ensure data quality, governance, and security across all business-critical data marts.

What they look for

SQL Data engineering AWS Amazon Redshift Data warehousing ETL Data modeling QuickSight Data quality GenAI Python Data governance Pipeline orchestration Semantic layer AWS Bedrock Data visualization

Requirements

Candidates must possess deep expertise in SQL, dimensional data modeling, and the AWS data stack including Redshift and QuickSight. Strong experience in pipeline orchestration, data quality frameworks, and working with GenAI/LLM services is essential for this role.

Benefits

Quarterly bonus scheme Flexible working Private health care Pension option

Full description

Department: Product Development

Location: Ireland (Dublin)

Employment Type: Full-Time, Permanent

Reports to: VP of Engineering

Work Model: Hybrid, 3 days per week in the Dublin office

Senior Data Engineers own the department's data integration and analytics platform, modelling data with SQL Transformation Layer on Amazon Redshift, curating the QuickSight / SPICE presentation layer, and integrating external sources such as Salesforce into the central data warehouse. They also make the warehouse and its semantic layer AI-ready, well-modelled, documented and governed so GenAI tooling (e.g. natural-language-to-SQL on AWS Bedrock) and downstream AI features can consume trusted data safely.

Key Objective / Role

Lead the design and delivery of data-enablement solutions on the AWS ecosystem, liaising with internal and external stakeholders to define and ship high-quality data pipelines that power our reporting and analytical capabilities. Own the Redshift warehouse, the RapidRatings ELT service and orchestration, the QuickSight semantic and reporting layer, observability and production data quality on business-critical marts, increasingly designing data products that power AI-native and internal GenAI tooling, in line with our AI-Driven Development Lifecycle (AI-DLC) delivery model.

Key Working Relationships

Product, Business and Operations stakeholders, requirements, data-quality reporting and sign-off.

Platform & Application engineering squads, AI / ML and platform initiatives such as Bedrock / GenAI tooling, semantic-layer definition and AI data-governance.

QA and external data providers for integration and end-to-end testing of data deliverables.

Essential Duties and Responsibilities

Design & operate the data warehouse and ELT: build, run and operate the AWS data warehouse and analytics environment; develop and maintain our SQL Transformation Layer on models across staging → intermediate → mart layers (incremental models, tests, auto-generated docs); integrate new external sources in and move curated data out to applications and affiliates, using GenAI to accelerate model/test generation under human review and CI guardrails.

Run the AWS analytics stack: operate Glue Data Catalog, S3 / Athena, Redshift and the QuickSight / SPICE presentation layer; build reports and visualisations; and manage performance and cost through retention / cold-archiving policies and query-performance tuning.

Orchestrate & observe pipelines: schedule, orchestrate and monitor batch / ELT jobs; manage job dependencies, failures and end-to-end pipeline observability.

Own production data quality: monitor and remediate mart-refresh and reconciliation defects on business-critical marts, and report data-quality status to product and business.

Apply governance, privacy & security controls: implement best-in-class security alongside PII anonymisation, right-to-erasure (member deletion / archival), dashboard-export restrictions and QuickSight group / permission management (RBAC).

Build the semantic / metrics layer: maintain the semantic layer and curated, documented datasets that serve as trusted context for GenAI tooling and downstream AI features.

Deliver AI-native data capabilities: deliver and operate natural-language-to-SQL / analytics-assistant capabilities on AWS Bedrock (RAG over warehouse metadata and lineage) with evaluation, guardrails, monitoring and cost controls (accuracy, hallucination and PII / data-leakage safeguards); and prepare feature-ready datasets and embeddings / vector stores that keep outputs explainable and auditable.

Mentor & collaborate: help engineers across the department troubleshoot SQL, Python and AI, acting as a strong technical collaborator who raises the team's overall data-engineering capability.

Key Competencies

SQL, data modelling & data warehousing: deep SQL and dimensional / data-warehousing expertise, with proven ETL/DWH delivery of end-to-end data integration for large-scale warehouses.

SQL Transformation & modern ELT modelling: hands-on SQL and modern ELT / warehouse modelling (dimensional and medallion-style layering).

AWS data stack: strong across Glue, S3, Athena, Redshift / PostgreSQL and QuickSight.

Orchestration, observability & data quality: pipeline orchestration, scheduling and observability, with ownership of production data quality, defect resolution and the maintenance of systems, processes, code and pipelines across varied sources and types.

Data management & quality frameworks: Data Quality Profiling, Metadata Management, Master Data Management and cleansing / standardising, with strong general data-manipulation skills (clean, transform, recode, merge and reshape).

Data visualisation: experience with visualisation tools (QuickSight, Power BI, Yellowfin), including advanced data visualisation and mapping.

Data governance, PII & RBAC: governance, PII handling and role-based access control in a regulated member-data environment.

GenAI / LLM for analytics: working knowledge of GenAI / LLM services (e.g. AWS Bedrock), prompt engineering, RAG and vector / embedding stores, and how to structure semantic / metrics layers so AI can query data reliably.

Why join RapidRatings?   Here at RapidRatings we foster an environment where employees feel recognised for their contributions, appreciated for their individuality, and challenged to do their best. We know that bringing together employees with different backgrounds, perspectives and experiences sparks innovation, promotes better decision making and yields the creative problem solving that’s critical to our long-term success. We offer an attractive benefits package with quarterly bonus scheme, flexible working, private health care, pension option and much more. With us, you are not just a number – we value people who are working hard and strive to make a real difference. Join our team to be a part of an industry-changing company and drive your career in the right direction.   

Would you like to know more about us and RapidRatings? Head over to our website: https://www.rapidratings.com/

Note: We have a great office in Dublin City Centre and offer remote / hybrid working. We understand each person’s circumstances may be unique and will work with you to explore suitable options.