• Data-Driven Culture: You will be an ambassador for our data-driven culture, taking data and shaping it to facilitate analysis, insight generation, and decision-making • Data Management: You will ingest, clean and organize raw data in a way that makes sense for both you and the team • Project Management: You will lead data projects from ingestion to reporting, showing your experience to oversee, scope, and work with ambiguity, making uncertainty certain • Collaborative Actualization: You will liaise between Business, Engineering, and Data to translate business requirements into proper data capture and schema design • Data Strategy: You will help shape the data model at Super, which will advance our broader analytics strategy and build trust within the organization • Teamwork: You will work with key stakeholders to understand existing processes and collaborate to design and implement improved and automated processes

• Set and raise the bar on analytics engineering standards. Define the patterns, testing, and review practices that keep dbt models across the business consistent, documented, and trustworthy without you personally checking every one. • Own the context layer. Bring the semantic layer (Omni) and the underlying domain models together into one place the business, human or AI, can query with confidence. • Build the domain model from first principles. Take tem's data from raw source to a structured, trusted layer that powers commercial, financial, risk, and operational decisions, not just dashboards. • Expand analytics engineering's reach across the business. Integrate new data sources, product and platform events, and the tools other departments run on, taking analytics engineering from a centralised function into new corners of the company. • Help tem think bigger. As the business looks at big bets like international expansion and new ways of bringing its technology to other companies, help build a domain layer that's ready to go with it. • Partner across the business, not just the data team. Work directly with engineers, product managers, and salespeople to understand what they're actually trying to achieve, then turn that into models that hold up under real use.

Role Description The operations team is a highly strategic and analytical team that helps guide and implement strategic initiatives across the company. We are looking for a Data & Analytics specialist to connect and organize our data across the company to drive visibility into performance and strategy across our sales, marketing, product, operations, finance, and engineering efforts. The ideal candidate will have some background in data engineering. - Design, build and maintain business-critical data and distributed systems that will provide real time and reliable data to for all of our go to market tools and internal users. - Connect our production backend/data to business systems including Salesforce, Marketo, Intercom, Google Analytics, Metabase, etc. This can include working with a data warehouse/data lake, organizing large scale data (we send 10 billion notifications a day), and building ETLs to business systems. - Evaluate ways to increase the efficiency of internal data flows and centralize sources of truth. - Innovate, design, and build data systems, services, and tools using GCP (Google Cloud Platform) that scale with OneSignal’s products and business requirements. - Work cross functionally including with the backend engineering team as well as business teams including operations, product, marketing, sales, customer success, support, finance, etc. - Analyze the data and create data insights and business insights to help move the business as well as assist and empower teams across the company in making data related decisions. - Build data science/machine learning models using internal and external data sources to identify potential new customers, those who are at risk of churn or those with potential upsell opportunities. - Work with Airflow, DBT, Presto, Hightouch and introduce the latest tools into our technology stack. Potentially, figure out how to incorporate artificial intelligence into our technology stack. Qualifications - 6+ years of professional experience in a technical area at a high growth startup is preferred. - Proficiency with Python and experience with DBT and Airflow is a plus. - Self driven and ability to identify problems and implement and identify solutions. - A combination of technical and business acumen. The ideal candidate would have an understanding of SaaS metrics and growth company infrastructure scaling challenges. - Strong interpersonal and communication skills and experience working cross functionally. - The ideal candidate has had experience growing and managing a smaller but high functioning team. Requirements - The New York and California base salary for this full time position is between $170,000 to $190,000. - Your exact starting salary is determined by a number of factors such as your experience, skills, and qualifications. - In addition to base salary, we also offer a competitive equity program and comprehensive and inclusive benefits.

• Lead the team responsible for building the trusted data foundation that powers decision-making across the company. • Oversee a team of analytics engineers who transform raw data into scalable, reliable, and well-governed data models. • Partner closely with Engineering, Product, Data Science, Finance, Marketing, Sales, Customer Success, and Executive Leadership to define our data strategy. • Balance technical excellence with business impact, helping the organization become increasingly data-driven while building a high-performing and inclusive team.