Location: Dublin
Reports to: CTO
Role Overview
We are seeking an experienced Senior Data Lead to play a pivotal leadership role in transforming our organization's data capabilities. This is a foundational position responsible for defining and delivering modern, scalable enterprise data architecture and analytics infrastructure while serving as a trusted partner to business units.
The ideal candidate will combine strong technical vision with excellent business acumen to bridge the gap between business needs and modern data solutions. You will be the key architect and change agent in establishing our next-generation data lake/warehouse ecosystem and enterprise data visualization & analytics platform.
Key Responsibilities
You will partner closely with business leaders, product managers, finance, operations, and other stakeholders to deeply understand business objectives, analytical needs, pain points, and strategic priorities, and lead a high-performing team of data engineers.
Responsible for translating business requirements into clear data & analytics strategies, roadmaps, and prioritized initiatives.
You’ll drive the evolution from legacy/reporting-focused systems to a modern, governed, scalable, and business-aligned data & analytics capability, including leading the design, architecture, and implementation of a modern enterprise data platform including:
Establishing a modern cloud data warehouse working with the CTO to select the most appropriate platform (Databricks, BigQuery, Databricks SQL, Redshift, etc.).
Define scalable data ingestion, transformation, and orchestration patterns.
Driving the definition and establishment of a future-state data visualization & business intelligence ecosystem, including:
Selection and implementation of enterprise visualization & BI tooling
Self-service analytics enablement strategy
Embedded analytics patterns (where applicable)
Governance, semantic layer, and "single source of truth" approach
You will establish and enforce data architecture standards, best practices, and patterns across the organization.
Define and track key success metrics for data platform adoption, data quality, time-to-insight, and business value delivered.
You will collaborate with infosec teams to ensure platform meets regulatory and security requirements (GDPR, CCPA, SOC2, etc.).
Required Skills & Competencies
8+ years of hands-on experience in data engineering, data platform architecture, or analytics leadership roles
Proven track record leading the design and implementation of modern cloud data lakehouse / data warehouse architectures at enterprise scale
Strong experience with at least one major cloud ecosystem (AWS, Azure, GCP) and their data services stack
Deep understanding of current data architecture paradigms (lakehouse, medallion architecture, data mesh principles, data virtualization, etc.)
Experience leading or heavily influencing enterprise BI/visualization platform selection and rollout (Looker, Power BI, Tableau, Sigma, ThoughtSpot, etc.)
Experience building and leading technical teams (5+ people preferred)
Excellent communication skills – ability to explain complex technical concepts to both technical and non‑technical audiences
Demonstrated success working in cross‑functional environments with strong stakeholder management skills
Bachelor’s degree in Computer Science, Engineering, Information Systems, or related quantitative field (Master’s preferred)
Strongly Preferred Qualifications
Experience with DataBricks
Experience working for a financial services, fintech, supplier risk, or a data provider
Previous experience establishing self‑service analytics programs with governance
Familiarity with modern data orchestration tools (Airflow, Prefect, Dagster, dbt Cloud, etc.)
What We Offer
Competitive salary and equity, comprehensive health benefits, flexible work arrangements (3 days in office per week) and a team that genuinely enjoys working together.
You’ll have real ownership over meaningful problems and the resources to solve them well.
At RapidRatings, you’ll work on challenging problems at the intersection of finance and technology, helping global enterprises make better decisions with data.
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