Data Analyst

We are looking for an experienced and results-driven Senior Data Analyst to join our Product – Data & Growth team. In this role, you will play a critical part in shaping Docker’s data strategy by leading the design, development, and optimization of data models, reports, and dashboards that support strategic business goals. You will collaborate with cross-functional teams to drive data-driven decision-making across the organization and mentor junior analysts to foster a culture of continuous learning.

This role is perfect for someone with advanced data analysis expertise, a passion for solving complex problems, and a track record of delivering impactful insights. The level of responsibility and scope will be tailored based on your experience and strengths, making it an ideal opportunity for professionals looking to advance their careers in data.

Key Responsibilities:

• Data Strategy & Execution: Lead data initiatives by designing, developing, and optimizing data models and reporting structures that support the organization’s strategic objectives.
• Data Analysis & Transformation: Conduct advanced data analysis, leveraging tools like Snowflake, DBT, and SQL to ensure accuracy, consistency, and actionable insights across various data sources.
• Data Modeling: Develop and maintain scalable, robust data models that enable both real-time and ad-hoc analysis, driving key business decisions.
• Reporting & Dashboards: Create, manage, and optimize dashboards and reports using Looker, providing stakeholders with clear, actionable insights.
• Collaboration: Partner closely with business teams, data engineers, and leadership to understand and meet data needs, aligning data initiatives with broader business goals.
• Mentorship & Team Development: Provide mentorship to other analysts, fostering professional growth and encouraging best practices across the team.
• Data Governance & Quality: Drive data quality initiatives, identifying and resolving inconsistencies while defining best practices for data governance.
• Continuous Improvement: Continuously refine and enhance data models, reporting pipelines, and processes to support evolving business needs and ensure scalability.

Key Skills and Qualifications:

• Experience: 5+ years of experience in data analysis, business intelligence, or a related field, with a proven ability to deliver impactful data solutions in fast-paced environments.
• Technical Expertise: Advanced proficiency in SQL and strong experience with data warehousing and ETL/ELT processes. Familiarity with Snowflake, DBT, and Looker is highly desirable.
• Analytical & Problem-Solving Skills: Strong analytical thinking with the ability to interpret data, identify trends, and generate actionable insights to inform business decisions.
• Communication: Exceptional communication skills, with the ability to distill complex technical concepts for both technical and non-technical audiences.
• Leadership & Mentorship: Experience mentoring junior team members and contributing to team development. Ability to influence and lead cross-functional teams in data-driven initiatives.
• Education: Bachelor’s or Master’s degree in a relevant field such as Data Science, Computer Science, Statistics, Economics, or Mathematics.
• Attention to Detail: A meticulous approach to data, ensuring accuracy and reliability in all deliverables, while maintaining a high standard of data quality.

What to expect in the first 30 days:

• Understand Docker’s Data Landscape: Deep dive into Docker’s data systems, processes, and business objectives to build a strong foundation for future contributions.
• Collaborate with Teams: Engage with cross-functional teams to gain insight into ongoing data initiatives and identify how you can contribute.
• Start Contributing: Begin taking ownership of smaller data analysis tasks, providing insights, and shaping solutions that align with business needs.

What to expect in the first 90 days:

• Lead Key Projects: Take full ownership of critical data analysis projects, ensuring they are aligned with strategic business goals and delivered on time.
• Collaborate Across Teams: Work closely with stakeholders to understand their data needs and deliver insights that directly impact business outcomes.
• Partner with Data Engineers: Collaborate with data engineers to ensure the scalability, reliability, and optimization of data pipelines and models.
• Execute and Deliver: Focus on delivering data solutions that meet timelines, driving execution, and continuously identifying areas for improvement in processes and systems.
• Mentor and Support: Provide mentorship to other data analysts, offering guidance and support in executing data projects while fostering a collaborative team environment

What to expect in the first year:

• Drive Large-Scale Initiatives: Lead and deliver large-scale data initiatives that meet business objectives and drive meaningful outcomes.
• Optimize and Evolve: Continuously optimize data models, dashboards, and reporting structures to support evolving business needs.
• Become a Key Contributor: Establish yourself as a strategic leader within Docker’s data team, driving data-driven decision-making and scaling processes to ensure long-term success.