Senior Analytics Engineer

United StatesRemoteFull-Timesenior

Data EngineerAnalytics EngineerDataData & AI

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Quick Summary

Overview

About Outreach Outreach, founded in 2014, is the only complete agentic AI platform for revenue teams. Outreach infuses agentic AI, conversation intelligence, and assistive AI to power hundreds of use cases across revenue motions.

Key Responsibilities

Technical Tools

airflowdbtpostgresqlsnowflakesqltableaudatabase-designetlforecasting

About Outreach

Outreach, founded in 2014, is the only complete agentic AI platform for revenue teams. Outreach infuses agentic AI, conversation intelligence, and assistive AI to power hundreds of use cases across revenue motions. From new logo prospecting to expansions, deal acceleration, driving retention, and forecasting, Outreach AI automates workflows and frees sellers to focus on more strategic conversations and actions. Revenue leaders benefit from connected account visibility, performance insights, and higher forecasting accuracy across every GTM team. World leading enterprise organizations use Outreach to power their revenue teams, including Databricks, SAP, Siemens, and Verizon to name a few.

About the Team

The Analytics Engineering team is dedicated to the empowerment of all people through the use of scalable and trusted data sets. We drive alignment on core business metrics and enable other teams to experiment with novel operational metrics to track the business. The AE team is a subset of the Business Systems team, and partners across the org to drive education and enablement for all employees.

The Role

As a Senior Analytics Engineer at Outreach.io, you will drive the success of Outreach’s Analytics and Operational programs through the production, documentation, and curation of certified data sources and models. You practice scalable coding practices, write efficient SQL, and document your work so that future stakeholders will already have their questions answered. You are the “T” in ELT (Extract-Load-Transform), and turn the data pipelines from our Data Engineering team into useful models for our Analytics and self service Data Champions to adopt and answer their own business questions. Overall, you make Data at Outreach.io a more trusted, governed, and powerful asset for all employees.

Location: We’re looking to hire this position remote within the US. #LI-Remote

Model and document new datasets (both structured and semi-structured) to exploit the value therein across all our business units

Partner with subject matter experts to document, align and automate business metrics that define success

Work with Analysts to optimize their use of data, either through query reviews, modeling exercises, or dashboard audits

Own the design, monitoring, and deployment of certified data sources on our reporting platforms and warehouses

Insist on the highest standards for data reproducibility, auditability and compliance

Serve as a subject matter expert for data strategy thought leadership and implementation across the business

Enable non-BI&A team stakeholders to adopt data as part of their business and usual

Ability to communicate complex concepts in a clear and concise manner to audiences from fellow analysts to senior executive level

Effective storyteller with an emphasis on visual best practices and discoverability

Expert SQL (Postgres/Snowflake Preferred)

History of working with or as a Business Analyst

Record of preemptive communication and documentation strategies favoring self-service education

Familiarity with Outreach tech stack: Snowflake, DBT, Airflow, Tableau, History of Query and Data Pipeline optimization

Have working knowledge with ML pipelines (i.e. Sagemaker)

Knowledge of multi-dimensional data modeling

Experience working in modern ELT environments

Code documentation best practices

Worked with business stakeholders for requirements gathering and documentation

Experience with Spark Ecosystem (Delta Lake, Databricks, etc.) is a plus

Experience in data modeling, schema design, and data quality best practices, with functional experience working on cloud platforms like Snowflake or Databricks is a nice to have.