Lead Data Engineer, Marketing Operations and Engineering
About The Position
The Marketing Operations and Engineering team in Growth Marketing and Insights (GMI) handles data architecture, transformation, and engineering for marketing measurement and insights. We manage backend data for attribution, customer segmentation, and lifetime value. We are looking for an Engineering Lead passionate about artificial intelligence. This role will evolve our data platform to support analytics, reporting, machine learning, and generative AI use cases. You will collaborate with business analysts, data scientists, and AI/ML teams to build scalable, AI-ready data systems that enable faster insights, automation, and intelligent decision-making.
Requirements
- BS/MS in Computer Science or equivalent experience with 8+ years of data engineering experience
- Strong expertise in SQL, Python, Spark, and modern data pipeline/orchestration tools (e.g., Airflow, dbt)
- Hands-on experience with cloud platforms (AWS, Azure, GCP) and modern data platforms such as Databricks
- Strong understanding of data modeling, data quality, governance, and scalable distributed systems
- Experience collaborating with data scientists and BI teams to deliver actionable insights and production-grade data solutions
- Exposure to AI/ML workflows and Generative AI concepts (e.g., embeddings, RAG, vector databases, LLM-powered applications)
- Experience using AI-assisted development tools (e.g., Cursor, Copilot, Claude) to improve engineering productivity
- Strong communication skills and ability to translate business needs into data and Technology-based solutions
Responsibilities
- Lead the design and development of scalable data pipelines, ETL/ELT processes, and data platforms that support analytics, marketing measurement, and AI/ML use cases
- Partner with business, data science, and engineering teams to define requirements, design architectures, and deliver high-quality data products
- Own and evolve the data platform to ensure data quality, governance, reliability, and efficient access for analysts, data scientists, and AI systems
- Re-architect and optimize data models and databases to improve usability, performance, and AI-readiness (semantic layers, feature-ready datasets)
- Drive adoption of AI-enabled workflows to accelerate development, automate insights, and improve operational efficiency
- Enable use cases such as automated reporting, conversational analytics, and intelligent decision support systems
Benefits
- comprehensive benefits programs
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Number of Employees
5,001-10,000 employees
