Principal Data Analyst - Analytics Products

Atrium (EMEA); Dublin; On-site; EUR 90,000 - 130,000; Full time

Job summary

Atrium (EMEA) is seeking a Senior Principal Data Analyst to drive complex data analysis for our analytics product portfolio in Ireland. You will translate business needs into scalable data solutions and work across Product, Data Engineering and Technology to validate outputs and ensure quality throughout discovery, development and launch.

As a hands-on contributor, you will shape data requirements, perform deep analyses, and present actionable recommendations to senior stakeholders, influencing

Qualifications

• Significant experience in data analysis, analytics or data-intensive product development.
• Strong hands-on analytical and problem-solving capability with complex datasets.
• Experience defining data requirements and translating business needs into analytical solutions.
• Strong experience with data validation, data quality assessment and root-cause analysis.
• Ability to interpret complex data patterns and derive actionable insights.

Responsibilities

• Lead complex data analysis for analytics products, capabilities and initiatives.
• Collaborate with Product Owners and Analysts to understand needs and outcomes.
• Translate requirements into data requirements, rules, measures and outputs.
• Assess data availability, quality, coverage and dependencies early in discovery.
• Translate analytical findings into recommendations for senior stakeholders.
• Define data requirements, mappings, transformations and business rules.
• Lead validation and support UAT to ensure outputs are accurate and reliable.
• Partner with Data Engineering to ensure solutions meet analytical needs.

Skills

Advance SQL

Python

Databricks

Data Quality Profiling

Automation

Job description

Leads complex data analysis for analytics products, defining data requirements, validating solutions and translating complex data into actionable insights to support scalable product development and informed business decisions.

The Principal Data Analyst will play a key role in the development and evolution of analytics product portfolio, supporting the development of net-new analytics products.

This is a senior, hands-on individual contributor role requiring strong analytical, data and problem-solving capabilities. The successful candidate will lead complex analytical work, define data requirements, assess data quality and feasibility, and translate complex datasets and business needs into scalable analytical solutions.

The role will work closely with Product, Business Analysis, Data Engineering, Technology, Architecture and business stakeholders, providing the analytical expertise required to take new products and capabilities from early discovery and feasibility through design, development, validation and launch.

Key Responsibilities

Data Analysis & Product Development

• Lead complex data analysis for assigned analytics products, capabilities and initiatives.


• Partner with Product Owners and Business Analysts to understand customer needs, business problems, use cases and expected outcomes.


• Translate business and product requirements into clear data requirements, analytical approaches, business rules, measures and expected outputs.


• Analyse complex datasets to identify patterns, opportunities, limitations and insights that inform product design and decision-making.


• Assess the feasibility of proposed analytics products and features, identifying data availability, quality, coverage and dependency considerations early in discovery.


• Develop deep subject matter expertise across assigned products, datasets and analytical domains.


• Translate complex analytical findings into clear recommendations for product and senior business stakeholders.

Data Requirements, Quality & Validation

• Define and document data requirements, data mappings, transformations, calculations and business rules.


• Work with Data Engineering and Technology teams to ensure data solutions meet agreed product and analytical requirements.


• Investigate data quality issues, anomalies and gaps and drive root-cause analysis and resolution.


• Define appropriate validation approaches and quality controls for new analytics capabilities.


• Lead analytical validation and support UAT to ensure outputs are accurate, reliable and aligned with customer and business expectations.


• Ensure data dependencies, assumptions and limitations are clearly understood and communicated.

Product & Delivery Partnership

• Provide analytical leadership throughout the product lifecycle, from discovery through delivery, validation, launch and continuous improvement.


• Partner with Product Owners and Business Analysts to shape data-driven product features and analytical propositions.


• Support estimation, planning and prioritisation by identifying analytical complexity, dependencies and risks.


• Work collaboratively with cross-functional teams to ensure analytical requirements are sufficiently defined before development begins.


• Support troubleshooting and resolution of complex data and product issues during development and following release.


• Identify opportunities to reuse data assets, analytical methods and capabilities across the wider product portfolio.

Data Governance & Scalability

• Ensure new analytics solutions consider data quality, governance, lineage and appropriate use of data.


• Partner with relevant Data Governance, Data Strategy and Technology teams to support compliant and scalable product development.


• Identify opportunities to improve data processes, analytical standards and reusable capabilities.


• Ensure analytical solutions are designed with appropriate consideration for scalability, maintainability and future product needs.

Stakeholder & Analytical Leadership

• Build strong relationships across Product, Business Analysis, Data, Technology and business teams.


• Act as a subject matter expert for assigned datasets, analytical capabilities and products.


• Communicate complex analytical concepts clearly to technical and non-technical stakeholders.


• Present analytical findings, risks, options and recommendations in a concise, decision-oriented manner.


• Provide analytical guidance to other team members and contribute to consistent standards and ways of working across the Data Analysis discipline.


• Proactively identify emerging data risks, opportunities and areas for improvement.

Technical skill requirements

• Advance SQL


• Python


• Databricks


• Data Quality Profiling


• Automation

Skills & Experience

• Significant experience in data analysis, analytics or data-intensive product development.


• Strong hands-on analytical and problem-solving capability, with experience working with complex datasets and business problems.


• Demonstrated experience defining data requirements and translating business needs into analytical solutions.


• Strong experience with data validation, data quality assessment and root-cause analysis.


• Ability to interrogate complex data and identify patterns, gaps, dependencies and insights.


• Experience partnering with Product, Business Analysis, Data Engineering and Technology teams.


• Experience supporting products from early discovery and feasibility through development, UAT and launch.


• Strong stakeholder management and communication skills.


• Ability to translate detailed analytical findings into clear business implications and recommendations.


• Strong attention to detail combined with the ability to understand the broader product and business context.


• Experience within healthcare, pharmaceutical, pharmacy or other complex data environments would be advantageous.