Data Engineer - ETL Developer

DATA ENGINEER – ETL DEVELOPER • • W2 contact, min 12 months • • REMOTE in the US • • Target W2 $85-100/hr • • The Engagement & Infrastructure (E&I) team provides a robust data and tooling ecosystem supporting our client’s Public Policy and Communications departments (PC). They manage a technology stack of both internal and 3rd party products and the data connecting them to enable successful policy, advocacy, compliance and reputational outcomes. Their team consists of experts in data engineering, AI/ML product development, geo-spatial data, CRM, government affairs operations and technology, marketing automation and research. This role will support Policy efforts by building, maintaining and improving upon integrated tooling and the ETLs underpinning much of our data operations. This will include performative data extracts, data pipeline design, and deep coordination with other data practitioners throughout the company as policy data intersects with numerous systems and teams. Responsibilities • Develop ETL processes to move third-party data into the data warehouse from data providers and vendors’ products where colleagues in Policy engage in project management and government affairs activities. • Configure data to be loaded and/or visualized into other environments, with a focus data piped into Salesforce CRM, prototyping apps that typically source data from Hive tables or S3, and Slack integrations to deliver alerts when anomalies are identified (viral social posts, regulatory/legislative announcements from local governments, relevant incidents in news articles). • Design, implement, and maintain data pipelines to connect Airbnb internal and external data. This foundational data set drives ML models that predict where legislative challenges/opportunities are likely to arise and the users most likely to engage politically. • Partner with Policy technical peers, Biztech Engineering, and Data Science to expand foundational policy data, connecting geospatial and core business metrics. Qualifications: • Expertise in ETLs, analytics, data engineering and data architecture • Expertise in Python • Expertise in SQL • Experience leveraging disparate data sets, in particular sales or marketing operations/legislative/regulatory/geospatial • Expertise in transforming data to be leveraged for self-service data visualization resources • Experience incorporating LLM calls into workflows and data pipelines • Talent for breaking down complex technical concepts into common language and acting as a bridge between technical and departmental stakeholders. • Experience working with complex and big data systems across a multitude of relationships and metrics. Ability to apply a creative and nuanced perspective to look beyond common data indicators in order to meet business goals. • Ability to self-serve and take the initiative to find answers to technical questions.