Requirements

Data Platform Development: Design, build, and manage scalable data pipelines and ETL processes to support a robust, analytics-ready data platform.
Cross-functional Collaboration: Partner with ai analysts, ml scientists, engineers and business teams to understand data needs and ensure accurate, reliable & ergonomic data solutions.
Data Strategy & Governance: Lead initiatives in data model development, data quality ownership, warehouse management, and production support for critical workflows.
Advanced Analytics & Insights: Conducted data analysis and built custom models to support strategic business decisions and performance measurement.
Automation & Optimization: Streamline data collection and reporting processes to reduce manual effort and improve efficiency.
Innovation in Data Infrastructure: Created scalable solutions like unified data pipelines and access control systems to meet evolving organizational needs.
Strategic Influence: Worked with partner teams to align data collection with long-term analytics and feature development goals.

Nice to Haves

Exposure to Apache Airflow or other DAG frameworks — we use Airflow to orchestrate and schedule all of our data workflows and transformations
Worked in Tableau, Looker, or similar visualization/business intelligence platform
Experience with operational tools and business systems such Google Analytics, Marketo, Salesforce, Segment, or Stripe
Familiarity with Python

Data Platform Development: Design, build, and manage scalable data pipelines and ETL processes to support a robust, analytics-ready data platform.
Cross-functional Collaboration: Partner with ai analysts, ml scientists, engineers and business teams to understand data needs and ensure accurate, reliable & ergonomic data solutions.
Data Strategy & Governance: Lead initiatives in data model development, data quality ownership, warehouse management, and production support for critical workflows.
Advanced Analytics & Insights: Conducted data analysis and built custom models to support strategic business decisions and performance measurement.
Automation & Optimization: Streamline data collection and reporting processes to reduce manual effort and improve efficiency.
Innovation in Data Infrastructure: Created scalable solutions like unified data pipelines and access control systems to meet evolving organizational needs.
Strategic Influence: Worked with partner teams to align data collection with long-term analytics and feature development goals.

Intercom has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.
We have a radically open and accepting culture at Intercom. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone.
Intercom values diversity and is committed to a policy of Equal Employment Opportunity.