Docker is a remote first company with employees across Europe, APAC and the Americas that simplifies the lives of developers who are making world-changing apps. We raised our Series C funding in March 2022 for $105M at a $2.1B valuation. We continued to see exponential revenue growth last year. Join us for a whale of a ride!
Docker is looking for a Senior Data Engineer to join our Data Engineering team which is led by our Director of Data Engineering. The team transforms billions of data points generated from the Docker products and services into actionable insights to directly influence product strategy and development. You’ll leverage both software engineering and analytics skills as part of the team responsible for managing data pipelines across the company: Sales, Marketing, Finance, HR, Customer Support, Engineering, and Product Development.
In this role, you’ll help design and implement event ingestion, data models, and ETL processes that support mission-critical reporting and analysis while building in mechanisms to support our privacy and compliance posture. You will also lay the foundation for our ML infrastructure to support data scientists and enhance our analytics capabilities. Our data stack consists of Snowflake as the central data warehouse, DBT/Airflow as the orchestration layer and Looker for visualization and reporting. Data flows in from Segment, Fivetran, S3, Kafka, and a variety of other cloud sources and systems. You’ll work together with other data engineers, analysts, and subject matter experts to deliver impactful outcomes to the organization. As the company grows, ensuring reliable and secure data flows to all business units and surfacing insights and analytics is a huge and exciting challenge!
Responsibilities:
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Manage and develop ETL jobs, warehouse, and event collection tools and test process, validate, transport, collate, aggregate, and distribute data
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Build and manage the Central Data Model that powers most of our reporting
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Integrate emerging methodology, technology, and version control practices that best fit the team
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Build data pipelines and tooling to support our ML and AI projects
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Contribute to enforce SOC2 compliance across the data platform
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Support and enable our stakeholders and other data practitioners across the company
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Write and maintain documentation of technical architecture
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