Job Title: Data Architect
Job type: Permanent
Job Location: Dublin/Hybrid
Company Overview:
A global data and artificial intelligence ("AI") company that offers services and solutions to reinvent client business models, drive better outcomes, and unlock growth with speed. The company harnesses the power of data, AI, and deep industry knowledge to transform businesses, including the world's leading corporations in industries such as insurance, healthcare, banking and financial services, media, and retail, among others. Founded in 1999, the company operates with the core values of innovation, collaboration, excellence, integrity, and respect.
The Role:
Experienced Data bricks Data Architect required to support a high-impact data transformation initiative focused on automating reporting and dashboard processes. You will work with structured and unstructured data sources, designing and building scalable ingestion and transformation pipelines within a Databricks medallion architecture.
The role will involve stakeholder engagement, defining data acquisition approaches, orchestrating bronze/silver/gold data pipelines and establishing best practices across governance, lineage, data quality, performance optimisation and release management. Strong hands-on experience with Databricks, modern data architecture and large-scale data processing environments is essential.
Key Responsibilities:
- Data Architecture & Medallion Design:
Design and evolve scalable data models within a Databricks Lakehouse architecture, structuring data across bronze, silver and gold layers to support reporting and dashboard automation. - Data Pipeline Design & Delivery:
Lead the design and implementation of data ingestion and transformation pipelines, working across structured and unstructured data sources to enable reliable, production-grade data flows. - Resident Client Engagement:
Act as a resident Data Architect on client site, working closely with stakeholders to understand requirements, shape data solutions, and ensure alignment to business outcomes. - Requirements Gathering & Translation:
Engage with business and technical stakeholders to gather, refine and define data requirements, translating them into scalable and maintainable data architecture designs. - Solution Evolution & Ownership:
Take ownership of the ongoing evolution of the data platform, continuously improving architecture, pipelines, and data structures in line with changing business needs. - Team Leadership (Onshore & Offshore):
Lead and guide distributed delivery teams (onshore and offshore), ensuring consistent standards, clear direction, and successful execution of data initiatives. - Data Governance, Lineage & Quality:
Establish and enforce best practices across data governance, lineage, metadata management, and data quality, ensuring trust and usability of data assets. - Performance & Optimisation:
Drive improvements in data processing performance, scalability, and cost optimisation, particularly within Databricks and distributed processing environments. - Standards & Documentation:
Define and maintain data architecture standards, models, and documentation, ensuring consistency, reusability, and alignment across delivery teams. - Delivery & Release Support:
Support deployment and release processes, ensuring data solutions are robust, properly governed, and production ready.
Experience Required:
- Education & Experience:
Bachelor's or master's degree in IT, Computer Science, or a related field, with significant experience (typically 8-10+ years) in data architecture, data warehousing, and large-scale data platforms, including hands-on experience in Databricks-led environments. - Data Modelling Expertise:
Strong experience in enterprise data modelling across conceptual, logical, and physical layers, ideally within data Lakehouse architectures (tools such as ERwin, ER/Studio, Power Designer or equivalent). - Databricks & Data Platform Expertise:
Proven hands-on experience designing and supporting Databricks-based data platforms, including medallion architecture, Spark-based processing, and scalable data pipelines. - Data Integration & Processing:
Experience delivering data ingestion and transformation solutions (batch and streaming) using tools such as Databricks, Azure Data Factory (ADF), or similar modern data integration frameworks. - Cloud & Distributed Data Environments:
Strong understanding of cloud-native data platforms (Azure preferred), including experience working with distributed data processing and integration with enterprise data stores (e.g., SQL Server, PostgreSQL, Oracle, Synapse). - Business Intelligence & Reporting Enablement:
Familiarity with reporting and visualisation tools such as Power BI, Tableau, or similar, with an understanding of how data architecture supports analytics and dashboarding. - Industry Experience (Desirable):
Experience within Insurance, Financial Services, or regulated environments is advantageous.
If you are interested in this role or would like to discuss it further, please call Nidhi at +353 1 645 5244 or email [email protected].
