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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # analytics engineer devops python sql - **Company:** HubSpot, Inc. - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $138,000.0 - $222,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Cloud Computing, Extract Transform Load (ETL), Data Transformation, Data Sharing, Data Structures, DevOps, Revision Control Systems, Python (Programming Language), Package Development Process, Software Engineering, SQL Databases, Systems Integration, Data Processing, Data Ingestion, Snowflake, Github Enterprise, Hubspot, Looker Analytics, Data Pipelines - **Published:** September 2, 2026 - **Apply:** https://www.workingnomads.com/job/go/1830777/ ## About the Role * Expert knowledge of modern data tools (such as Snowflake, dbt, and Looker) * Extensive proficiency in SQL, data modeling, ETL, ELT, and data transformation * Deep dbt expertise including advanced modeling patterns, macros, and package development * Experience developing slowly changing dimension (SCD) tables from multiple sources * Successful experience leading complex, cross-functional data initiatives from ambiguous problem to production * Experience building or maintaining shared data platform assets, developer toolkits, or internal frameworks * Experience designing semantic models or metric layers for analytics or AI consumption * Proficiency with AI-assisted development tools such as Claude Code, including agentic pipeline design and composable, skill-based workflows * Comfort building AI agents and integrating external tools and services via MCP servers * Experience utilizing version control tools (such as GitHub Enterprise Cloud) * A DevOps mindset characterized by automation, collaboration, continuous improvement, and a hyperfocus on user needs and frequent iteration * Strong communication skills and ability to distill technical solutions into business terms * Experience with Python is a plus, but not required ## Description HubSpot's mission is to Help Millions of Organizations Grow Better. HubSpot's Operations team is core to this goal by supporting the HubSpotters who drive growth and serve HubSpot's customers. Our goal in Operations is to embed advanced analytics and algorithmic intelligence into the DNA of decision-making across HubSpot. Flexible, well-connected, well-architected data are the backbone of our strategy, along with the Analytics Engineers who create that landscape. In this role, you'll join the Data & AI Foundations team to design and build a modern data foundation for efficient models and analyses. Your work will directly support analytic and ML products that change the way we make decisions across HubSpot. You'll bring a strong interest in building flexible, reusable architecture for our highest-value data assets, while also shaping the internal tooling, agentic workflows, and standards that make the entire AE team more effective and scalable. In this role, you'll get to: * Build and optimize the performance of data pipelines and analytical tools for scale * Own and evolve core platform assets, AE tooling, reusable patterns, and automation that raise the floor for every AE on the team * Contribute to our composable agentic AE delivery system, a pipeline of AI-powered skills that automates the full delivery lifecycle from context to merged PR * Design and maintain semantic models that serve as the trusted, reusable foundation for analytics and AI consumption across the organization * Build internal AI agents and data-grounded tools, integrating RPC-based capabilities via MCP servers * Design and implement cost strategies for shared data assets, pipelines, and compute usage * Define and deploy scalable data ingestion, replication, and transfer patterns across systems * Foster innovation with emerging technologies and by staying current with industry trends * Guide professional development of the team through technical leadership * Partner with stakeholders to solve business problems with technical solutions * Build out scalable data models to analyze key parts of the HubSpot business * Expand our suite of dbt patterns and macros to enable flexible and easily extensible data structures * Drive data observability and pipeline reliability using tools like Monte Carlo * Establish scalable patterns and standards for analytical application development in Hex * Lead working groups, scope requirements, and usher projects through the entire lifecycle * Maintain detailed documentation of data pipelines, processes, and best practices, HubSpot may use AI to help screen or assess candidates, but all hiring decisions are always human. More information can be found here. By submitting your application, you agree that HubSpot may collect your personal data for recruiting, global organization planning, and related purposes. We may use CLEAR ID Verification during the hiring process to confirm your identity and help maintain a safe, secure, and trusted experience for all candidates. 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