Job Description
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Company Overview
An AI-native automation company focused on transforming how enterprises operate through intelligent agents and adaptive software. Its platform enables AI agents to understand real-world workflows, execute tasks across business systems, and continuously improve through usage. The technology supports operational workflows across functions including IT, HR, Finance, Security, Legal, and Engineering.
The company works with organizations across technology and other industries to automate high-volume, repetitive operational processes and is building an AI-driven operations layer designed to provide greater leverage across modern businesses.
Responsibilities
- Build and own the company’s first unified data warehouse, including data modeling, pipelines, data quality, and performance.
- Partner with teams across the organization to translate ambiguous business questions into clear requirements, standardized metrics, and actionable data solutions.
- Consolidate data from production PostgreSQL databases and SaaS platforms covering product usage, CRM, marketing, billing, support, and finance into a centralized source of truth.
- Build systems that make clean and reliable data available within the tools used by business teams.
- Design performant data models with clear lineage, standardized naming conventions, and comprehensive documentation to support self-service business intelligence.
- Develop internal data tools using applied AI to turn recurring data questions into self-service insights and answers.
- Establish data quality, governance, and security practices from the beginning of the data function.
- Evaluate vendors, tools, and data architecture while maintaining a lean and cost-conscious technology stack.
- Establish data engineering practices, standards, and processes that can support future team growth.
- Collaborate closely with Engineering, Product, go-to-market, and operations teams to ensure the data infrastructure supports business decision-making and product needs.
- Act as a strategic data partner by understanding business requirements and delivering insights that support effective decision-making.
Qualifications
- 5+ years of experience in data engineering and business analytics, with hands-on experience building and maintaining data warehouses and data pipelines.
- Expert-level SQL skills, including practical 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 platforms such as Snowflake, Databricks, or comparable technologies.
- Experience developing ETL/ELT pipelines using modern data tools such as Fivetran and dbt.
- Hands-on experience with AWS and infrastructure-as-code technologies such as Terraform.
- Demonstrated ability to own data projects end to end and make sound technical decisions independently.
- Experience serving as an early or first data hire is a plus.
- Strong product intuition and business curiosity, with the ability to translate business questions into well-structured data models and meaningful metrics.
- Ability to collaborate effectively with both technical and non-technical stakeholders.
- Comfortable working in a fast-growing startup environment characterized by rapid execution and ambiguity.
Disclaimer
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