Data Analytics Engineer (Marketing)

Overview

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Band 6 – Data Analytics Engineer (Marketing)

As part of the Thermo Fisher Scientific team, you’ll do meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life—enabling customers to make the world healthier, cleaner, and safer.

We are seeking an Analytics Engineer to manage and evolve the data foundations powering the LSG Search (SEO + SEM) and cross-channel marketing analytics. This role handles massive volumes of marketing and customer data to unlock performance insights at scale.

Sitting at the intersection of data engineering and analytics, this position focuses on transforming diverse marketing data sources into reliable, automated, and performance-optimized datasets within BigQuery. You will lead complex data initiatives, architect scalable pipelines, apply advanced analytical techniques, and convert complex, open-ended business questions into clear, actionable insights for marketing channel managers and business partners.

Responsibilities:

• Lead hands-on development of API integrations, Python-based ETL data pipelines, and analytics workflows across platforms such as Google Ads, Bing Ads, Adobe Analytics, STAT, Botify, GSC and SEMRush to enable reliable marketing data access
• Write production-quality SQL against large datasets and contribute to version-controlled analytics workflows using GitLab/GitHub
• Develop and maintain advanced analytical models, forecasts, and attribution frameworks, applying techniques such as time-series analysis, causal inference, experimentation, and machine learning to marketing and customer behavior problems
• Build and maintain Looker dashboards, Adobe workspaces, automated reports, and ad hoc analyses to surface keyword opportunities, evaluate channel performance, and guide spend and investment decisions
• Partner with marketing stakeholders to translate ambiguous business questions into well-defined analytical solutions, clearly communicating insights to both technical and non-technical audiences
• Provide informal mentorship and technical guidance to junior analysts and engineers, encouraging teamwork and technical excellence
• Deliver technical documentation and code reviews to uphold data team standards and maintain knowledge continuity
• Continuously identify opportunities to improve data quality, analytics workflows, and reporting efficiency, leveraging AI, automation, and traditional optimization methods
  
  

• Bachelor’s Degree plus 4+ years of experience in marketing analytics, data engineering, applied data science, or a related field
• Expertise in ETL/ELT tools, data warehousing, and cloud-native platforms such as Databricks, Snowflake, or BigQuery
• Deep understanding of data modeling, metadata management, and data governance frameworks
• Demonstrated hands-on experience developing analytical or machine learning models and applying data science techniques to real-world marketing or business problems
• Strong technical proficiency in SQL and Python or R, with experience working in large cloud data warehouse environments
• Working knowledge of causal inference, experimentation, time-series analysis, and forecasting methodologies
• Solid understanding of digital marketing fundamentals and metrics, including CPA, ROAS, CVR, attribution, segmentation, and channel performance
• Experience working with marketing analytics and BI tools (e.g., Adobe Analytics, Google Analytics, Power BI, Looker)
• Strong organizational skills with a proven ability to manage multiple priorities in a collaborative, team-oriented environment
  
  

• Experience with BI tools, GitLab/GitHub-based analytics workflows, and modern analytics engineering practices
• Exposure to marketing automation platforms, experimentation frameworks, or advanced analytics tooling
  
  

• Proactively create solutions as opportunities are identified
• Fluency in English; additional language skills are a plus
• Excellent written and oral communication skills, including ability to communicate across business areas and with executive leadership