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Health-E Commerce

Analytics Engineer

Posted 19 Days Ago
Remote
Hiring Remotely in United States
75K-100K
Mid level
Remote
Hiring Remotely in United States
75K-100K
Mid level
The Analytics Engineer will build data pipelines, develop interactive dashboards, and conduct statistical analysis to drive business strategy using data insights.
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About the Role:  

We are looking for an Analytics Engineer to join our growing Analytics team. The Analytics Team at Health-E Commerce is a centralized shared service using data to help guide the company towards making the right decisions, addressing challenges, and identifying new opportunities to grow. The Analytics team sits under the SVP of Data Science and Analytics, and is tightly integrated with the Data Engineering and Data Science Functions, as well as with various cross-functional stakeholders in Marketing, Sales, Finance, and Product. The Analytics Engineer role will focus on building out data pipelines, building interactive dashboards, and conducting statistical analysis to inform business strategy through data-driven insights.  We are a highly visible team working to support the business in the most impactful ways possible, and committed to teamwork, cross-collaboration and career development for our team members! 

What you’ll do:

  • Build data pipelines and data models through ETL/ELT processes in collaboration with the Data Engineering team to better serve business insights 
  • Define, develop and implement dashboards and reporting to ensure ongoing progress and status updates. 
  • Create informative and well-organized presentations that contribute to overall business needs and goals, explaining complex situations clearly and simply. Be a translator of complex data into concise, actionable business insights 
  • Ensure data robustness, accuracy and governance across all pipelines and views 
  • Identify opportunities for department-wide improvement and communicate with management to recommend and effectuate change. 
  • Support new strategy, processes design, and communications in collaboration with cross-functional teams 
  • Fulfill ad-hoc requests for data and analysis 

What you'll need:

  • Bachelor’s degree in Computer Science, Mathematics, Statistics, Economics, Business or related fields; advanced degrees and/or specializations a plus  
  • 2+ years of experience in analytics, data science, data engineering, business intelligence, or related function 
  • Advanced knowledge of modern BI and data visualization tools with a strong preference for Microsoft Power BI end to end development
  • Knowledge of data modeling and data engineering in various cloud environments (both data warehouse and data lakes) such as BigQuery, Microsoft Fabric, Snowflake, etc.
  • Intermediate to advanced knowledge of SQL (Non TCL/DCL)
  • Python proficiency highly preferred
  • Comfortable with a range of statistical techniques ranging such as regression analysis, probability, survival modeling, etc.
  • Ability to communicate effectively with wide-range of audiences 
  • Ability to quickly ramp up on new tools/software 
  • Passion for data and its fundamental ability to create value 
  • Extremely curious and excited to dive into complex problems  

Additional Details:

At Health-E Commerce, our goal is to provide an offer that supports growth potential within the role and allows for future salary progression. Final compensation is evaluated on various factors which include but aren’t limited to experience, skills, internal equity among peers, and geographic location. 

  • Compensation: $100,000 - $125,000
  • Discretionary Annual Bonus Eligibility: Up to 10%
  • Medical, Dental, Vision, and 401K with a company match
  • Dependent Care, FSA & HSA accounts
  • Paid Parental & Bonding Leave
  • Flexible PTO & office closure on all major holidays
  • Monthly wellness & internet reimbursements
  • Professional development including certification support & leadership coaching
  • Mental Health resources
  • 100% remote within the United States
  • Must be able to work EST hours

Top Skills

BigQuery
Microsoft Fabric
Microsoft Power Bi
Python
Snowflake
SQL

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