United States onlyAbout Outreach
Outreach, founded in 2014, is the only complete AI Revenue Workflow Platform that helps sales leaders benefit from connected account visibility, performance insights, and higher forecasting accuracy across every GTM team. Outreach infuses agentic AI to power 100s of use cases across sales motions. From new logo prospecting to renewal and expansion, Outreach AI automates workflows and frees sellers to focus on more strategic conversations and actions. Global organizations use Outreach to power their revenue teams, including SAP, Siemens, Snowflake, ZoomInfo, and Verizon to name a few. To learn more, please visit www.outreach.io.
About the Team
Data is at the core of Outreach's strategy. It drives our product and our customers to the highest levels of success. We use it to derive customer health scores and revenue dashboards, monitor operational metrics of our AWS infrastructure, increase product engagement and user productivity through natural language understanding, and power predictive insights and causal inference via experimentation. As our customer base continues to grow, we are looking towards new ways of leveraging our data to deeper understand our customers’ needs and deliver new products and features to help continuously improve their customer engagement workflows.
The Business Systems Data Engineering team is on a mission to bring relevant data to every person at Outreach while advancing the use of data and promoting an insight-centric culture. We are a centralized resource providing a suite of services to Outreach business functions across Finance, Analytics, and Support systems, with data as the critical component to a seamless experience.
Our Vision of You
- Data is your passion, from schema design to understanding data pipelines to data validation and optimization. You love everything about data and live in this world.
- You strive to become an expert in analytics toolchains and solutions (such as Databricks, Python, Spark) and understand their nuances as you optimize schemas to take advantage of their unique features.
- You are meticulous about data and data-pipeline quality and obsessive about building solutions that verify data correctness at every step of the pipeline
Basic Qualifications
- 3+ years of Data Engineering experience
- Excellent communication and collaboration skills.
- Passionate about working cross-org to understand business requirements and drive decisions about how to best deliver value.
- Good understanding of RDBMS and NoSQL data stores and when to use each
- Experience with OLAP and OLTP type datastores including schema design and query optimization
- Experience working with processing large amounts of data
- Experience with distributed bus systems (Kafka, RabbitMQ)
- Strong skills in at least one programming language languages (Python, Ruby, Golang)
- Experience with Spark Ecosystem (Presto, Delta Lake, Databricks, etc.)
- You embody our core values: we are hungry craftspeople, we have grit, we are honest, we take ownership, we have each other’s back no matter what, we’re one with our customers, and we find strength in diversity and inclusion
We’re an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
Our success is reliant on building teams that include people from different backgrounds and experiences who can elevate assumptions and ideas with fresh perspectives. We're dedicated to hiring the whole human, not just a resume. To that end, we look for a diverse pool of applicants-including those from historically marginalized groups. We would like to invite you to apply even if you don't think you meet all of the requirements listed below. We don't want a few lines in a job description to get between us and the opportunity to meet you.
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