We're looking for an experienced Data Engineer to work on our massive data processing pipeline and our new NextGen BI system to help us deliver more insights and scale from our current billion events a day to tens of billions of events.
Responsibilities:
Pull data from various data sources and integrate into the ETL process
Integrate Machine Learning models in ETL to deliver insights to Marketing, Product and CRM departments
Optimize workloads to reduce cost and improve performance
Work closely with analysts from Product, Marketing and Data Scientists to deliver insights from over a Billion daily events and over 50 Marketing channels.

he Business Data Engineering Lead is responsible for transforming raw data into actionable insights that drive business decisions across company functions (executive leadership, Sales, Marketing, Finance, People, etc). This role involves extracting and integrating data from various sources, building ETL pipelines, calculating key metrics, and developing visualizations to support strategic decision-making. The ideal candidate combines technical expertise with business acumen and strong communication skills to bridge the gap between data and business needs.
Responsibilities:
Collaborate with executives and business teams (sales, marketing, finance, HR, operations) to understand data needs and translate them into analytical solutions.
Extract, clean, and integrate data from various sources, including databases, data warehouses, and external systems.
Design, build, and maintain ETL pipelines to ensure efficient data processing and transformation.
Develop and calculate key performance metrics (KPIs) tailored to business objectives.
Create clear and compelling dashboards and visualizations to communicate insights effectively.
Perform data analysis to identify trends, opportunities, and risks that inform strategic decision-making.
Ensure data accuracy, consistency, and integrity across all reporting and analytics efforts.
Continuously improve data models, workflows, and reporting processes to enhance efficiency and scalability.
Stay up to date with industry trends and emerging technologies in data engineering and business intelligence.
Educate and support business stakeholders in using data-driven insights for better decision-making. Provide analytical insights beyond just providing the data.