Senior Data Engineer

Morgan McKinley; Cork; On-site; EUR 70,000 - 110,000; Full time

Job summary

Morgan McKinley seeks a Senior Analytics Engineer / Lead Tableau Developer for a critical 6-month contract. You will lead Tableau dashboards, migrate Tableau Cloud, and support Snowflake migration within a modern data stack using Snowflake and dbt.

You will partner with executive leadership to translate reporting requests into scalable analytics products, establish governance, and deliver high-quality data insights.

Qualifications

• 5+ years of experience in business intelligence, data analytics engineering, analytics development, or related discipline.

Responsibilities

• Analytics & Front-End Development: Design, develop, and maintain Tableau dashboards translating complex data into intuitive visuals.
• Standards & Governance: Create reusable templates, KPI definitions, analytics patterns and enable self-service analytics.
• Data Modelling: Build analytics-ready datasets, semantic models, and business logic with advanced SQL.
• Full-Stack Troubleshooting: Understand data architecture and pipelines to debug performance across the stack.
• Stakeholder Partnership: Translate reporting requests into scalable, trusted analytics products for leadership.

Skills

Advanced SQL

BI/Analytics

Stakeholder partnership

Tools

Tableau

Snowflake

dbt

Python

REST APIs

Job description

We are seeking an ambitious, proactive, and highly skilled Senior Analytics Engineer / Lead Tableau Developer for a critical 6-month contract.

• Tableau Cloud Migration: Migrate three on-premise Tableau instances to Tableau Cloud, while leading a comprehensive upgrade and rebranding initiative for our core reporting assets.


• Snowflake Migration: Support the strategic separation of our reporting layers from transactional databases via a migration to Snowflake.


• Modern Architecture: Work within a modern data stack structured around a Medallion Model using Snowflake and DBT for data transformation.

Role Breakdown

• 10-20%: Broader Back-End Data Platform, Pipeline, & Infrastructure Integration

Key Responsibilities

• Analytics & Front-End Development: Design, develop, and maintain sophisticated Tableau dashboards that translate complex datasets into intuitive, visually compelling, and actionable user experiences.


• Standards & Governance: Establish reusable dashboard templates, visual standards, KPI definitions, and analytics design patterns while enabling appropriate self-service analytics.


• Data Modelling: Develop and maintain analytics-ready datasets, semantic models, calculated measures, and business logic using advanced SQL.


• Full-Stack Troubleshooting: Bring enough back-end engineering experience to understand the underlying data architecture, data models, and pipelines to independently investigate performance issues across the full stack.


• Stakeholder Partnership: Partner closely with executive leadership and business functions to convert loosely defined reporting requests into scalable, trusted, and intuitive analytics products.

Required Skills & Experience

• Experience: 5+ years of experience in business intelligence, data analytics engineering, analytics development, or a related discipline.


• Industry Exposure: Prior experience working within Healthcare, Clinical Supply Chain, or other highly regulated data environments is highly preferred.


• Advanced SQL: Expert-level SQL writing (window functions, complex joins) and experience optimizing workbook load times using Hyper extracts and query tuning.


• Cloud Data Platforms: Hands-on experience with modern cloud data platforms, specifically Snowflake (AWS Redshift, Databricks, or BigQuery also considered).


• Mindset: An ambitious, proactive, and curious mindset. You uncover the true business decision a stakeholder is trying to make and design the simplest, most effective analytical solution for it.

Desired Skills (Nice to Have)

• Hands-on experience with dbt (data build tool) for data transformation.


• Python or R for scripting, automation, and data analysis.


• Familiarity with REST APIs, JSON, and CI/CD practices for analytics assets.


• Daily use of AI coding assistants (e.g., Claude Code, Cursor, GitHub Copilot) to accelerate development workflows.