Senior Analytics Engineer, Docker
$147.2-184k
Salary applicable to US only. Offers equity
More information about location
App development platform
Be an early applicant
App development platform
501-1000 employees
Be an early applicant
$147.2-184k
Salary applicable to US only. Offers equity
More information about location
501-1000 employees
Company mission
To increase the time developers spend on innovation, and decrease the time they spend on everything else.
Role
Who you are
- Experience: 5+ years of experience in data engineering or analytics engineering roles, with a proven track record of leading complex data projects and initiatives
- Technical Expertise: Deep expertise in SQL, DBT, and data modeling, with a strong understanding of data pipeline design, ETL processes, and data warehousing
- Software Engineering Skills: Proficiency in software engineering principles, including CI/CD pipelines, version control (e.g., Git), and scripting languages (e.g., Python)
- Data Tools Proficiency: Hands-on experience with tools like Snowflake, DBT, and Looker. Familiarity with additional tools and platforms (e.g., AWS, Kubernetes) is a plus
- Problem-Solving: Strong analytical and problem-solving skills, with the ability to diagnose and resolve complex technical issues related to data infrastructure
- Leadership: Demonstrated ability to mentor and lead junior engineers, with a focus on fostering a collaborative and high-performance team environment
- Communication: Excellent communication skills, with the ability to clearly and concisely convey complex technical concepts to both technical and non-technical stakeholders
- Education: Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
What the job involves
- As a Senior Analytics Engineer, you will be immersed in our data model, taking ownership of the construction of data pipelines, foundational reporting structures, and data models that support key business objectives
- You will be responsible for solving complex data challenges, transforming data into valuable insights, and mentoring junior team members while contributing to the strategic direction of our data initiatives
- Data Pipeline Leadership: Design, develop, and maintain highly scalable and efficient data pipelines, ensuring timely and accurate collection, transformation, and integration of data from various sources
- Advanced Data Modeling: Architect and implement robust data models and data warehousing solutions that enable efficient storage, retrieval, and analysis of large, complex datasets
- Cross-Functional Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand data requirements, translating them into actionable data models and insights
- Data Quality Assurance: Implement and oversee rigorous data validation, cleansing, and error-handling mechanisms to maintain high data quality and reliability
- Performance Optimization: Continuously monitor and optimize data pipeline performance, identifying and resolving bottlenecks and inefficiencies to maintain optimal system responsiveness
- Mentorship and Leadership: Provide guidance and mentorship to junior analytics engineers, fostering a collaborative and learning-oriented environment
- Strategic Contribution: Contribute to the strategic direction of data initiatives, staying abreast of industry best practices, emerging technologies, and trends in data engineering and analytics
- Documentation & Knowledge Sharing: Build and maintain user-facing documentation for key processes, metrics, and data models to enhance the data-driven culture within the organization
- Tool and Technology Expertise: Serve as a key expert in tools such as Snowflake, DBT, and Looker, ensuring they are leveraged effectively to meet business needs
- What to expect in the first 30 days:
- Get to know Docker! Familiarize yourself with our vision, mission, values, and product offerings
- Complete all required onboarding and training sessions
- Gain access to necessary systems, databases, and platforms
- Familiarize yourself with our tech stack and internal processes
- Shadow team members to learn about our development workflows
- Meet with key stakeholders and team members to understand projects and OKRs
- Perform initial data pipeline and modeling tasks, and review our documentation to become familiar with key data assets
- What to expect in the first 90 days:
- Achieve a deep understanding of key data models, pipelines, and reporting structures
- Take ownership of key data engineering projects, driving them from inception to delivery
- Provide regular mentorship and support to junior engineers, fostering a collaborative team environment
- Participate in peer reviews and pair programming sessions
- Build and update documentation for key processes, metrics, and data models
- Triage incoming data requests, scoping and delegating tasks as needed
- Lead complex modeling initiatives and data pipeline optimizations
- Foster strong relationships with key stakeholders across the organization
- What to expect in the first year:
- Lead initiatives to optimize data pipelines, reducing processing times and enhancing data accuracy
- Establish and maintain high standards for data quality, reducing inconsistencies and ensuring reliable data delivery
- Mentor and lead a small team of analytics engineers, managing their priorities and deliverables
- Contribute significantly to Docker’s data strategy, helping shape the future of our data infrastructure
- Develop and refine robust data governance practices, ensuring compliance and alignment with business objectives
- Drive the creation of an analytics knowledge base, serving as the single source of truth for key metrics and data processes
Our take
Docker supplies a hub and desktop solution to simplify the workflow of app development teams. Originally known for popularising the idea of containerising software, it saw itself outpaced by Kubernetes. However, the company has identified a problem with the growing complexity of containerisation, with some apps consisting of dozens or even hundreds of containers - which is what it now addresses.
Docker has had a difficult time in the recent past, with 2019 seeing it sell off its enterprise business, reduce its workforce by hundreds, and change its leadership team. As a well known brand and ecosystem for containerisation, however, it aims to lure developers back to its product as well as to take advantage of the growing global demand for app development.
Returning to focus on developers rather than large companies was certainly a gamble, but one that seems to have paid off. The company has returned to profitability and raised Series C funding in 2022, which is cited to fund hiring new talent, ramping up its business, and continuing to develop and refine its product. It's also embarked on a series of acquisitions to
Steph
Company Specialist
Insights
Company
Funding (last 2 of 10 rounds)
Mar 2022
$105m
SERIES C
Mar 2021
$23m
SERIES B
Total funding: $497.9m
Company benefits
- 100% company paid medical premiums for employees and dependents
- Flexible Time Off Policy
- “Whaleness” Days — At least 1 company wide day off per month
- Employer Paid Holidays
- Generous Maternity and Parental Leave
- Home Office Set Up Budget
- Monthly Technology Stipend
- Training Allowances
- Life and Disability Insurance
- Retirement Plans
- Virtual and In-Person Social Events
- Docker Swag
- Quarterly Hackathons
- Virtual Coffee with Co-Workers
Company values
- Humility - We give credit rather than seeking it. We’re always open to feedback and correction. We don’t assign blame when something goes wrong, but learn from it together
- Developer Obsession - We understand developers, we put developers’ priorities first, and we never get in their way. We succeed by making developers happy and productive
- Open Collaboration - We’re very open internally about what’s going on, good and bad. Almost all documents and conversations are visible to everyone. Transparency is key. We help each other’s teams and departments, rather than building our own empires
- Bias for Considered Action - We don’t do things carelessly or without thinking, but we want to move fast, and we encourage our employees to act proactively and autonomously. We prefer to take action sooner, and iterate or correct as necessary. Experiments are good
Company HQ
China Basin, San Francisco, CA
Articles
Leadership
Scott Johnston
(CEO, not founder)Has been COO and CPO with Docker prior to CEO role. Before that was VP, Marketing & Product at Puppet and a Venture Partner at Alloy Ventures.
Diversity, Equity & Inclusion at Docker
- Docker embraces diversity and we’re wholeheartedly committed to being proactive in promoting diversity across our organization. We’re dedicated to establishing an organization that reflects the fundamental respect for different ways of working and living, and we assure every Docker employee the opportunity to reach his or her full potential.
- Current Employee Groups (with more to come!): Women ERG, Mental Health ERG, DEI Council
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