Senior Staff Software Engineer, Data Platform

Outreach is the first and only AI Sales Execution Platform built for intelligent revenue workflows. Built on the world’s largest foundation of customer interactions and go-to-market team data, Outreach’s leading revenue AI technology helps go-to-market professionals and their companies win by intelligently accelerating decision-making and elevating sellers to do their best work. Our powerful platform gives revenue teams the tools they need to design, measure, and improve a revenue strategy for every stage of the customer journey, improving efficiency and effectiveness across the entire revenue cycle. Over 6,000 customers, including Zoom, McKesson, Snowflake, SAP, and Okta use Outreach to power workflows, put customers at the center of their business, improve revenue results, and win in the market.

The Role

Data is at the core of Outreach's strategy. It drives our customers and ourselves to the highest levels of success. We use it for everything from customer health scores and revenue dashboards to operational metrics of our AWS infrastructure, to helping increase product engagement, to predictive analytics and causal inference via experimentation. As our customer base continues to grow, we are looking towards new ways of leveraging our data to save our customers time and improve their sales efficiency.

About the Team

The mission of the Data Platform team is to accelerate the success of our internal and external customers through trustworthy data analysis and experimentation. We eliminate data silos and democratize data through effective data ingestion, curation, governance, and serving. As a Senior Staff Software Engineer, you will play a critical role in building and maintaining ourdata platform. You will be responsible for defining our strategy, delivering data-driven functionality, and shipping end-user features. You will work alongside a talented team of software engineers, data scientists, and product managers to transform the way our customers do business.

Your Daily Adventures Will Include

• Design and implement our cutting-edge data platform, harnessing state-of-the-art technologies and innovative best practices to deliver unparalleled performance, scalability, and reliability, effectively propelling our data capabilities to new heights
• Build sophisticated data pipelines that power our data analytics, GenAI, machine learning, and business intelligence applications, enabling our customers to make data-driven decisions
• Implement robust data security and privacy measures, ensuring that our sensitive data is protected from unauthorized access and breaches
• Implement systems tracking and monitoring data integrity, data quality, and consistency
• Collaborate closely with other engineering teams to seamlessly integrate our data platform components into our software applications, creating a seamless user experience
• Develop framework & tools to support self-service data pipeline management
• Mentor and train junior data engineers, sharing your knowledge and expertise to help grow the team

Basic Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field
• At least 8 years of experience in software engineering and data engineering, with a focus on designing and building data platforms
• Strong experience with data processing frameworks, such as Spark or Hadoop
• Strong programming skills in Python, Ruby, or Go
• Strong experience with cloud-based data platforms, such as AWS or GCP
• Experience with data modeling, data warehousing, and ETL processes
• Experience with modern Lakehouse table formats; such as Delta Lake, Apache Iceberg, Apache Hudi
• Good understanding of SQL languages(s) and ability to conduct advanced performance tuning
• Experience with infrastructure management, such as Kubernetes and Terraform
• Experience with workflow management tools
• Experience with data security and privacy measures
• Excellent problem-solving skills and attention to detail
• Strong communication skills and ability to work effectively in a fast-paced startup environment