Analytics Engineer
Our data team works hand-in-hand with stakeholders across every Replicated team to better understand our business through the data, and to enable data-informed decision making by creating analyses, reports, and tools.
We strive for creating value through data– not only delivering high quality datasets and reporting, but pairing with stakeholders to understand the problem being solved, and ensuring the solution has an impact on the business. Our teammates spend time embedding within the other teams at Replicated to get the full context behind projects, while also working together to come up with ways to find answers in our data.
What you'll be doing:
- Partnering with stakeholders on our Product, Engineering, Revenue, and Finance teams to drive better organizational decision making, provide data insights, and build data products.
- Contributing to end-to-end projects and analyses that answer key questions about the business. These projects may involve defining the problem, acquiring and analyzing the right data, and then communicating findings to a broad range of stakeholders.
- Examples of projects include assessing customer health based on how they use our software, identifying indicators of success during the customer onboarding process, and measuring the impact of product changes on how much support our customers need.
- Maintaining deliverables, projects, and timelines for your business stakeholders.
- Advocating for improvements to our data platform that have an impact in data quality, security, and performance for our team and the organization.
- Helping to define and improve our internal standards and processes for delivering insights to the business.
What you bring to the role:
- Experience as a "full stack" data analyst or analytics engineer– helping generate business insights and supporting better organizational decision making.
- Demonstrated and/or Professional experience working with SQL and Git. Python experience is a plus.
- Working knowledge of the modern data stack. We use Snowflake, dbt, Looker, and Hex.
- Clear and direct communication skills about complex technical topics.
- A record of working autonomously with strong organizational and time management skills.
How you'll ramp:
By the 30 day mark, you'll be...
- Working in our BI tool and writing SQL to pull data from our data warehouse
- Aware of how our data platform works and what problems we’re working on solving with our business stakeholders
By the 60 day mark, you'll be...
- Comfortable working with dbt via the command line
- Comfortable answering questions on your own
- Contributing to internal conversations on data organization and structure
By the 90 day mark, you'll be...
- Collaborating with team members to get answers out of our data and our data tools
- Owning part of our data platform (e.g. data source, report, infrastructure component)
- Regularly contributing to documentation and housekeeping improvements for the team
In the US, the salary range for this role is as follows:
- Analytics Engineer: $150,000 - $165,000
- Sr. Analytics Engineer: $160,000-$180,000