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Manager – Analytics Engineering
Confirmed live in the last 24 hours
San Francisco, CA, USA
Experience Level
Desired Skills
Data Analysis
Data Science
  • 3+ years of data science, analytics and/or data engineering leadership experience
  • Experience working with software and data engineering teams, an understanding of the software development lifecycle, what drives software team to succeed and exposure to typical software engineering tools (e.g. Jira, SCM, CI/CD systems)
  • Expertise in data modeling, (e.g. SQL, Python), knowledge of cloud data environments (e.g. AWS), and experience with data ETLs and UAT processes
  • An Agile development mindset, appreciating the benefit of constant iteration and improvement. A very high bar for output quality, while balancing "having something now" vs. "perfection in the future"
  • Experience applying your analytics skills to identify and lead projects that have had impact on strategic and product roadmap decisions
  • A very high bar for output quality; with experience coaching teams to balance thoughtfulness, perfection and speed
  • Expertise in SQL and proficiency in another data science programming language (e.g Python, R)
  • Proficiency in at least one visualization tool (e.g. Tableau, R-Shiny, dash, Microstrategy)
  • Comfort explaining complex concepts to diverse audiences (such as Product Managers, Designers, Engineers), and creating compelling stories
  • Project management and prioritization experience; preferably with Data Engineering, Product Management, and Software Engineering teams
  • A degree in a quantitative discipline (e.g. statistics, mathematics, physics, engineering, computer science, econometrics)
  • Draw on your expertise in understanding software development lifecycle and developer productivity to think about what are data and insights features that we should ship to our customers to influence the way they work
  • Partner with the data engineering and platform teams to identify, and support short, medium and long-term portfolio of projects that improves data assets used across data science
  • Envision, scope, and lead projects by collaborating with partners, software and data engineering leaders, and data scientists
  • Guide the creation of tools that allow a centralized data framework that improves the efficiency, quality and capabilities of all data analysts and scientists
  • Oversee business case development, data requirement gathering (including metrics and definitions agreement), establishing acceptance criteria, QAing, and testing for new transformational data products from start to finish to ensure everything is implemented and validated
  • Work across marketing and product to develop monitoring and action plans across the data quality lifecycle (instrumentation → transformation → data/metrics/segments)
  • Lead, coach, and build the data quality team within the Data Science team
  • Collaborate with the Business Intelligence team to define and achieve standard segment and metric definitions and governance
  • Contribute into overall Data Science team OKRs
  • Be part of building an outstanding analytics culture at Atlassian. Leading by example, through education and creation of self-service tools, to make a lasting change in how data is used to make decisions
  • Guide demos sessions and education roll out for new data products and features to ensure adoption and usage

5,001-10,000 employees

Software tools for development & project management
Company Overview
Atlassian's mission is to help unleash the potential of every team. The company operates software tools – JIRA, BitBucket, Trello, and more – for team and project management.
  • Health insurance
  • Vision insurance
  • Dental insurance
  • Life insurance
  • Flexible or health savings accounts
  • Short-term disability insurance
  • Long-term disability insurance
  • Retirement savings plans
  • Paid time off
  • Catered lunches, wellness reimbursements, onsite fitness
Company Core Values
  • Open company, no bullshit - Openness is root level for us. Information is open internally by default and sharing is a first principle. And we understand that speaking your mind requires equal parts brains (what to say), thoughtfulness (when to say it), and caring (how it’s said)
  • Build with heart and balance - “Measure twice, cut once.” Whether you're building a birdhouse or a business, this is good advice. Passion and urgency infuse everything we do, alongside the wisdom to consider options fully and with care. Then we make the cut, and we get to work
  • Don’t #@!% the customer - Customers are our lifeblood. Without happy customers, we’re doomed. So considering the customer perspective - collectively, not just a handful - comes first
  • Play, as a team - We spend a huge amount of our time at work. So the more that time doesn’t feel like “work,” the better. We can be serious, without taking ourselves too seriously. We strive to put what’s right for the team first – whether in a meeting room or on a football pitch
  • Be the change you seek - All Atlassians should have the courage and resourcefulness to spark change – to make better our products, our people, our place. Continuous improvement is a shared responsibility. Action is an independent one