Role Overview
As a Data Engineer, you’ll help scale our Global Enterprise Analytics capabilities by developing, implementing, and maintaining robust data pipelines, systems, and models to enable data-driven decision-making across global client engagements.
What You Will Do
Design, develop, and maintain complex, scalable data pipelines and systems to process large volumes of data efficiently, collaborate with cross-functional teams, and build dashboards, reports, and visualizations to clearly communicate technical insights and metrics.
Why It Might Be a Fit
We are looking for someone who thrives in cross-functional, agile environments, pairs technical precision with strong communication, and is passionate about mentoring junior team members while turning complex data streams into actionable business intelligence.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Operations Research, Statistics, Applied Mathematics, Economics, Engineering, Physics, or equivalent quantitative practical experience.
- 3+ years of experience across analytics, marketing analytics, and analytic techniques for customer and business applications.
- Strong programming proficiency in SQL, Python, or R, combined with solid experience working with SQL and NoSQL databases.
- Hands-on experience with Google Cloud Platform (GCP), Google BigQuery, and common ETL tools (e.g., Funnel.io, Tableau Prep).
- Proven expertise building dashboards using tools such as Tableau, Looker, Google Looker Studio, Power BI, or Datorama.
- Deep understanding of analytics platforms (Google Analytics, Adobe) and ad tech/media reporting APIs and UIs (DV360, SA360, Meta).
- Proven aptitude for agile methodologies, DataOps pipeline delivery, and operating effectively both autonomously and within collaborative teams.
- Advanced/fluent English communication skills (written and spoken) to support teams and stakeholders in the US and globally.
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