Senior Data Engineer, Growth, Insights & Analytics

Key Responsibilities

• Cloud Data Infrastructure & Platform Engineering
• Lead and own the design, development, and optimization of scalable cloud-based data pipelines and architectures (AWS, Azure, or GCP) to support enterprise analytics, reporting, and data science initiatives
• Build and manage a modern data platform (lakehouse architecture) leveraging technologies such as Snowflake, Databricks, Redshift, or BigQuery, enabling high-performance analytics and data accessibility
• Collaborate with IT and Architecture teams to align on cloud strategy, data infrastructure, and enterprise technology roadmaps
• Data Integration & Media Analytics Enablement
• Integrate and manage diverse data sources, including retailer POS, syndicated data (e.g., Nielsen/Circana), e-commerce, ERP systems, and retail media platforms (e.g., Amazon Marketing Cloud, Walmart Luminate, Kroger Precision Marketing)
• Develop and optimize pipelines for ingesting and transforming retail media, digital advertising, and campaign performance data (e.g., Amazon Ads, DSP, paid search, social platforms)
• Develop scalable and reusable data models, APIs, and curated datasets to support self-service analytics and business intelligence tools (e.g., Power BI)
• Data Governance, Quality & Advanced Capabilities
• Ensure high standards of data quality, governance, security, and privacy compliance, implementing monitoring, metadata management, and lineage tracking
• Continuously evolve data engineering capabilities, including adoption of real-time/streaming pipelines (Kafka, Spark Streaming), automation frameworks, and AI-ready data infrastructure

Required Education, Skills and Experience

• Bachelor’s degree required; advanced degree preferred
• 6–8+ years of experience in Data Engineering, Data Platforms, or a related technical field
• Experience designing and building cloud-native data pipelines and architectures (ETL/ELT)
• Strong proficiency in SQL and Python (or similar languages such as Scala or Java)
• Hands-on experience with cloud platforms (AWS, Azure, or GCP) and modern data stack tools including Snowflake, Databricks, Airflow, dbt, Fivetran, or similar
• Experience working with API-based data ingestion and integration frameworks, particularly for digital media and retail platforms
• Demonstrated ability to transform complex, high-volume data into clean, scalable, and usable datasets
• Experience implementing data governance, quality frameworks, and observability tools
• Strong communication and stakeholder management skills, with the ability to translate technical concepts into business-friendly language
• Familiarity with CPG and omnichannel data ecosystems, including retailer POS, syndicated data (IRI/Nielsen/Circana), and digital commerce data sources
• Hands-on experience with retail media and advertising data platforms, including: Amazon Marketing Cloud (AMC); Amazon Ads / DSP; Walmart Luminate, Kroger Precision Marketing, or CitrusAd (Criteo Retail Media); Paid media platforms (Google, Meta, TikTok)
• Experience enabling MMM, retail media measurement, or marketing analytics use cases
• Knowledge of data modeling techniques for marketing, media, and commercial analytics
• Experience with real-time or streaming data pipelines (Kafka, Spark, or similar)