Job Description
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Company Overview
An AI-native automation platform is transforming how enterprises operate by building intelligent agents that understand real-world workflows and execute them end-to-end. The platform is designed to replace manual processes and rigid legacy systems with adaptive, learning software.
Founded in 2024, the organization is trusted by companies across technology, media, and business services to automate high-volume and high-friction operational work. Its agentic AI platform transforms natural-language requests into production-grade workflows, enabling agents to reason, take actions across systems, and continuously improve through usage.
The platform has expanded beyond operational use cases into a horizontal AI automation layer supporting functions including IT, HR, Finance, Security, Legal, and Engineering. The organization’s mission is to reduce repetitive manual work across enterprises and provide teams with greater leverage through intelligent automation.
Key Responsibilities
- Build and own the company’s first unified data warehouse, including data modeling, pipelines, data quality, performance, and ongoing maintenance.
- Treat the data warehouse as a core company product that teams can reliably use for decision-making and analytics.
- Partner with teams across the business to translate ambiguous questions into clear requirements, standardized metrics, and actionable data solutions.
- Consolidate data from production PostgreSQL databases and SaaS systems covering product usage, CRM, marketing, billing, support, finance, and other business functions.
- Establish a single source of truth for company data and enable clean data to flow back into the tools used by business teams.
- Design clean and performant data models with clear lineage, standardized naming conventions, and comprehensive documentation.
- Build a self-service BI foundation that enables teams to access and understand trusted data independently.
- Develop internal data tools using applied AI and intelligent agents to turn recurring data questions into self-service answers.
- Own data quality, governance, and security from the beginning and establish practices that scale with the organization.
- Make informed decisions regarding vendors, tooling, architecture, and build-versus-buy strategies.
- Maintain a lean and cost-conscious data technology stack.
- Establish data engineering practices, standards, and processes that can serve as the foundation for a growing data team.
- Collaborate with Engineering and Product teams to ensure data infrastructure supports both internal business intelligence and product requirements.
Required Qualifications
- 5+ years of experience in data engineering and business analytics.
- Hands-on experience building and maintaining data warehouses and data pipelines.
- Expert-level SQL skills, including hands-on experience with PostgreSQL.
- Strong Python skills for pipeline development, scripting, and internal tooling.
- Experience building a modern data warehouse or lakehouse from the ground up using technologies such as Snowflake, Databricks, or comparable platforms.
- Experience designing and maintaining ETL/ELT pipelines using modern data tools such as Fivetran and dbt.
- Hands-on experience with AWS and cloud-based data infrastructure.
- Experience using Terraform or other infrastructure-as-code technologies to manage cloud infrastructure.
- Demonstrated ability to own data projects end-to-end and make sound technical decisions independently.
- Experience working as an early or first data hire is preferred.
- Strong product intuition and business curiosity, with the ability to translate business questions into useful and scalable data models.
- Ability to identify meaningful business metrics and establish reliable measurement frameworks.
- Strong communication and collaboration skills when working with both technical and non-technical stakeholders.
- Comfortable operating in a fast-paced environment with ambiguity and evolving priorities.
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