Job Description & How to Apply Below
Location: Bengaluru
This job is with Thermo Fisher Scientific, an inclusive employer and a member of my Gwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.
Work Schedule
Standard (Mon-Fri) Environmental Conditions
Office
Job Description
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 ting 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 Big Query.
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 Git Lab/Git Hub
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 work spaces, 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
Requirements:
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 Big Query
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
Preferred
Experience with BI tools, Git Lab/Git Hub-based analytics workflows, and modern analytics engineering practices
Exposure to marketing automation platforms, experimentation frameworks, or advanced analytics tooling
Knowledge, Skills, Abilities:
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
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