Senior Data Engineer

Rapid Ratings International Inc.; Dublin; Hybrid; EUR 95,000 - 115,000; Full time

Benefits offered by this job

Health insurance via RapidRatings

Workplace pension with matched贡献 up to

25 days PTO

Job summary

RapidRatings is seeking a senior data platform engineer to lead design and delivery of data-enablement solutions on AWS, owning the Redshift warehouse, ELT services, and the QuickSight layer. You will collaborate with product, operations, and engineering to define scalable data pipelines powering reporting and AI-native tooling, while ensuring data quality and governance.

The role is hybrid in Dublin, Ireland, reporting to the VP of Engineering, with 3 days/week in the office and close

Qualifications

• Deep SQL and dimensional/data-warehousing expertise with end-to-end ETL/DWH delivery.
• Experience integrating new external sources and building scalable data pipelines.
• Ability to design data products for AI-native tooling and GenAI workflows.

Responsibilities

• Design, operate and optimize the AWS data warehouse and ELT pipelines across staging to mart layers.
• Maintain SQL transformation layer, models, tests and auto-generated docs.
• Orchestrate batch/ELT jobs and ensure end-to-end pipeline observability and data quality.

Skills

SQL & data warehousing

ELT modelling

AWS data stack

Orchestration & observability

Data quality frameworks

Data visualisation

RBAC & data governance

GenAI for analytics

Tools

AWS Glue

S3

Athena

Redshift

QuickSight

Job 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

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.

About RapidRatings

RapidRatings is a leading fintech company providing enterprises with the financial health intelligence they need to manage supplier risk, protect working capital, and build more resilient supply chains. We serve global organisations across manufacturing, consumer goods, financial services, and infrastructure. We’re growing fast.

Our Values

Integrity, Innovation, Accountability, Resilience, Community

Some of our Benefits:

• Health insurance via RapidRatings with a generous allowance.


• Workplace pension with matched contributions up to 5%.


• 25 days of paid time off (PTO)

Pay Transparency Statement (Ireland)

In line with the EU Pay Transparency Directive, we are committed to openness about compensation.

Salary Range: €95,000 to €115,000 base salary (Dublin, Ireland)

RapidRatings International Inc. (“RapidRatings”) is proud to be an equal opportunities employer. We do not discriminate based upon race, religion, color, national origin, sex, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We may access publicly available information as part of RapidRatings review of your application. This online application feature is hosted in the United States by RapidRatings, Inc., and we may process your application and information relating to you in the United States, Ireland and other RapidRatings locations, as we deem appropriate under the circumstances.

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