Senior Analytics Engineer, Go-To-Market

Posted 19 days agoViewed

💎 Seniority level: Senior, 5+ years

📍 Location: United States

💸 Salary: 157300.0 - 255200.0 USD per year

🔍 Industry: SaaS

🏢 Company: Calendly👥 501-1000💰 $350,000,000 Series B about 4 years ago🫂 Last layoff over 1 year agoProductivity Tools Enterprise Software Collaboration Meeting Software Scheduling Software

🗣️ Languages: English

⏳ Experience: 5+ years

🪄 Skills: PythonSQLCloud ComputingETLGitSalesforceSnowflakeAPI testingData engineeringCommunication SkillsAnalytical SkillsCI/CDProblem SolvingRESTful APIsAttention to detailCross-functional collaborationData visualizationStrategic thinkingData modelingData analyticsData managementSaaSA/B testing

Requirements:

5+ years of experience working with a SaaS company, partnering with the GTM domain, and building data products in a cloud data warehouse (BigQuery, Snowflake, Redshift, Databricks, etc.)
Expert SQL skills with strong attention to data accuracy and integrity (R or Python is a plus)
Experience owning a dbt project with engineering best practices (e.g., unit testing, data quality checks, reusable building blocks, etc.)
Hands-on experience with Segment for web event tracking and customer data integration
Experience with version control systems like Github, Bitbucket, Gitlab, etc (bonus for CI/CD pipeline management)
Proficiency in data modeling to meet business and GTM needs for today, and beyond
Ability to diagnose data issues proactively and build trust in data across GTM teams
Experience with website experimentation (A/B testing, personalization, CRO analysis)
Experience with Salesforce, Braze, and paid ad platforms, ensuring seamless GTM data flow
Experience implementing and driving adoption of data quality tools, like Monte Carlo, or similar anomaly detection tool
Strong growth mindset—you understand how data drives revenue, acquisition, and retention

Responsibilities:

Design scalable queries and data syncs to provide customer traits, event data, and insights for GTM teams
Build customer journey models to drive lead prioritization, retention strategies, and precision targeting
Support web, CX, and content teams in implementing and analyzing experiments, personalization, and conversion optimizations
Drive adoption of Monte Carlo for GTM data monitoring and issue resolution, ensuring high trust in insights
Ensure timely and reliable data availability across Salesforce, Braze, Segment, and paid media platforms
Establish data governance and analytics engineering (AE) best practices, aligning with the core data platform and Analytics teams
Collaborate closely with Marketing, Sales, CX, Ops, and Analytics teams to ensure data is leveraged effectively for business decisions

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