• Build and maintain scalable data models in dbt that support reporting and analysis across Company Pillar teams • Develop well-structured, reusable datasets in Snowflake • Build and maintain reporting assets in Looker to enable self-serve analytics • Support internal teams by improving data definitions, reliability, and usability • Assist with root-cause analysis of data issues and implement sustainable fixes • Strengthen documentation around data models, definitions, and requirements • Grow your analytics engineering toolkit through peer collaboration and learning within HubSpot’s AE community

• Develop and maintain ETL processes to support data ingestion, transformation, and integration. • Work with various file formats (TXT, CSV, XML, JSON, YAML) to ensure seamless data processing. • Implement and optimize ETL workflows using EasyMorph, Databricks, Azure Data Factory, Talend, and Apache Nifi. • Write clean, efficient, and maintainable code using Python, C#, or Java. • Ensure data quality, accuracy, and integrity across ETL pipelines. • Collaborate with data engineers and analysts to define and refine ETL requirements. • Troubleshoot and resolve ETL failures, ensuring minimal downtime and impact. • Follow test-driven development (TDD) methodologies to improve reliability and maintainability. • Maintain and document ETL processes, providing insights and recommendations for improvements.

Salve is seeking a Data/Analytics Engineer to own the BI modeling layer and dashboards for our regulated-industry analytics product (with a focus on cannabis). You’ll translate business questions into performant SQL, design and maintain semantic/data models, and build polished dashboards and self-serve reports in our BI platform. You’ll partner closely with customers and internal teams to customize reporting, ensure data quality and governance, and turn complex datasets into clear, actionable insights. Additionally, you will work closely with the data engineering team to ensure data ingestion, modeling and reporting quality. Responsibilities Build and maintain the semantic layer/metrics: define KPI logic and reusable models that power dashboards and self-serve reporting. Test and improve data modeling for generative AI. Translate business questions into performant SQL and polished dashboards in our BI tool; ship clean, drill-friendly reports. Work directly with customers to customize reporting and data workflows. Optimize warehouse and query performance for fast, cost-effective analytics. Help implement and monitor ETL/ELT to land and transform data from databases, files, and APIs (e.g., Hevo, Airbyte, Glue). Manage schema changes and migrations with version control and backward-compatible rollouts. Develop and deploy forecasting models (e.g., regression, time-series) to power forecasting reports and alerts. Triage and resolve reporting issues and pipeline incidents; drive root-cause analysis and prevention. Work with customer success and onboarding to manage and document customer implementations onto the platform. Required Skills & Experience Strong proficiency in SQL. Hands-on experience with relational databases and data warehouses, especially Snowflake, MySQL and Postgres. Understanding of data modeling principles (star/snowflake schema, normalization/denormalization). Experience building ETL/ELT and data processing pipelines using tools such as dbt, Hevo, Airbyte, Glue, or Spark. Experience with data visualization tools such as Omni, Metabase, PowerBI, Looker, Mode, etc. Excel-capable. Strong troubleshooting skills. Preferred Skills Experience with Python. Familiarity with data orchestration tools such as Airflow or Dagster. Experience using generative AI models, especially using Snowflake Cortex. Knowledge of AI, machine learning and MLOps, especially for forecasting and classification. Experience with building and maintaining web scrapers. Familiarity with PHP and Laravel. MUST reside between UTC-4 (EST) & UTC-7 (PST) Time Zones Desired Skills Strong communication skills with the ability to explain technical concepts clearly Comfortable leading client calls and presenting data findings Proactive, responsive, and focused on delivering a great customer experience Collaborative team player who works well across technical and non-technical teams Organized and adaptable, able to manage multiple client engagements and troubleshoot on the fly Salve Team Fit At Salve , we believe small teams can make a big impact. Our work is driven by a passion for innovation, a commitment to excellence, and a strong collaborative spirit. Every voice matters here — we show up each day ready to collaborate, tackle challenges, and grow together while we do meaningful work that improves lives. At Salve, we strive for the right balance — it’s not a place to fade into the background or to dominate the conversation. We value individuals who lead with humility, prioritize the team, and contribute to shaping our vibrant and supportive culture. We’re looking for someone who shares our values and thrives in a fast-paced, evolving environment. Our ideal teammate is: An excellent communicator who brings clarity and empathy to every interaction. A hard-working self-starter who loves tackling new challenges and isn’t afraid to jump in. Resilient and adaptable in a fast-moving landscape. A problem-solver at heart , turning obstacles into opportunities. Known for a positive attitude , bringing energy and optimism to their team. A true team player who supports, inspires, and celebrates the success of those around them. If you believe that small teams can do big things — and you want to grow alongside a driven, supportive crew — we’d love to hear from you.

• Design and implement scalable, efficient Data Products that drives business value within our GTM product. Examples include sales heatmap & overall efficiency; quotas & attainment; revenue attribution; marketing attribution; marketing spend efficiency; Reverse ETL from product to SFDC. • Collaborate with stakeholders and GTM data scientists to understand business requirements and translate them into clear, actionable data outputs through effective data modeling. • Improve time to insight by preparing SSOT data models as a core input for analysis in Sigma, our preferred BI tool. • Optimize data pipeline systems from a variety of sources, ensuring data is accurate, timely, and consistent, Sample tools: hubspot, salesforce, talkdesk, marketing platforms. Make sure our Product / backend systems have a proper linkage with GTM systems. • Improve GTM data quality, sharing data integrity guidelines, highlighting current issues, and collaborating with different stakeholders on implementation of proper fixes.