Analytics Engineering Manager
virtual vocationsDenver (CO)
About the role
To enhance data science quality and velocity, the full-time Analytics Engineering Manager II will build and lead a diverse team, develop best practices for data instrumentation, and create AI tools and analysis pipelines, working remotely with occasional in-office collaboration.
Key responsibilities:
Build, inspire, and grow a high-performance team of analytics engineers while fostering an inclusive culture
Develop best practices for data instrumentation and experimentation, collaborating with product engineering teams
Utilize AI to accelerate analysis and automate documentation processes, ensuring data quality and correctness
Required qualifications:
6+ years of experience in a data-driven environment, including management of engineering teams
Proficiency in SQL and a scripting language (Python or R) for manipulating complex datasets
Experience with workflow orchestration and ETL/ELT processes involving large datasets
Demonstrated ability to translate open-ended goals into defined objectives and actionable insights
Bachelor's, Master's, or PhD in a quantitative field or equivalent experience
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
It's what we read first. Occupations, seniority and locations matter more than a long history.
Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
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