Data Engineer, Ads Finance, Ad Sales Analytics, Ads Sales Analytics
1 week ago
Key job responsibilities
- Owning the design, operations and improvements for the Organizations Datawarehouse infrastructure
- Maintain, improve and manage all ETL pipelines and clusters
- Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
- Define metrics and KPIs to measure success of strategic initiatives and report on their progress
- Develop relationships and processes with finance, sales, business operations, solution delivery team, partner, BD, and other cross-functional stakeholders
- Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
- Collaborate with data scientists, BIEs and BAs to deliver high quality data architecture and pipelines.
- Design extensible metrics schemas that support complex analytical queries while optimizing for AI retrieval patterns.
A day in the life
In this position the successful candidate will be responsible for partnering with Finance and Business leaders to expand and optimize data infrastructure that supports weekly, monthly, quarterly and annual for the Display Ads Finance group and our stakeholders. They will work on building GenAI capabilities and GenAI-ready data layer for automating insights generation and solving analytical problems across the Ad Sales FInance org.
About the team
The Advertising Sales Finance Analytics & FP&A team's responsibilities comprise of corporate reporting, planning, Headcount & OpEx, Goals reporting, and ad-hoc analysis. We support Advertising leaders and finance teams by coordinating and consolidating deliverables, centralizing and standardizing processes, establishing financial controls and mechanisms, building tools that improve the speed of decision making, and providing insightful financial analysis on the short and long term strategy of Advertising.
- 5+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Knowledge of distributed systems as it pertains to data storage and computing
- Experience in ETL management/data pipeline
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- 5+ years of SQL experience
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Knowledge of cloud computing services or deployment architecture
- Experience building data pipelines or automated ETL processes
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