Senior Analytics Engineer

Key Skills

AWS, Azure, Cloud computing, Data Analytics, Data Modeling, Data Visualization, Design, Effective communication skills, Github, Lambda, Machine learning techniques, PySpark, Python Programming, Snowflake, Tableau

Job Description

ResMed has always applied the best of technology to improve people's lives. Now our SaaS technology is fueling a new era in the healthcare industry, with dynamic systems that change the way people receive care in settings outside of the hospital–and tools that work every day to help people stay well, longer. We have one of the largest actionable datasets in the industry, creating a complete view of people as they move between care settings. This is how we empower providers–with vital insight to deliver the care people need, right when they need it.

We're also ensuring that our health solutions connect to other companies' networks. Because when objectives align, everyone wins. And as we work today to drive better care and lower costs, we're developing more personalized solutions for tomorrow, utilizing machine learning, intelligent care paths, and predictive protocols. If you are an innovator who wants to make an impact we want to talk to you! We have exciting opportunities supporting Brightree by ResMed and MatrixCare by ResMed!

Analytics Engineer

Job Summary

At ResMed, Analytics Engineering is how we make our invaluable data available and accessible to the people and systems that need it, as we develop and deliver solutions that cater to the unique needs of our customers and patients. Analytics Engineers make our data more useful by building robust, efficient, and integrated data models and analytics products that support every part of our company.

Our Analytics Engineers are part of a centralized, but dedicated group of expert analytics practitioners, all working in support of ResMed’s business strategy and objectives. As such, they are required to be equally skilled in the tools and methods of analytics development as they are in the contextual particulars of the business domain to which they are dedicated. Technical expertise, in combination with business acumen, is the collective, aspirational skill set that enables our Analytics Engineers to continually identify and build highly impactful and scalable solutions.

Let’s talk about Responsibilities

• Use data modeling expertise to enable other analytics practitioners through code reviews, pairing, and training to help deliver optimal, DRY, and scalable database designs and queries in Snowflake
• Collaborate with team members to collect business requirements, define successful analytics outcomes, and design data models
• Design, develop, and extend dbt code to extend the Enterprise Dimensional Model
• Craft code that meets our internal standards for style, maintainability, and best practices; maintain and advocate for these standards through code review
• Approve data model changes as a part of review processes, and act as an owner for specific database and data model schemas
• Design, develop, and extend analytics solutions that maximize impact and utility for data users and consumers
• Build data models that minimize the cognitive and technical overhead that is required to find and use analytical insights
• Maintain subject matter expertise in the application and usage of our data as well as our analytics technologies and tools

Let’s talk about Qualifications and Experience

Required (Qualifications/experiences that are an absolute must for the position)

• 5+ years of experience in Data & Analytics as an analyst, engineer, or equivalent
• 4+ years of experience designing, implementing, operating, and extending enterprise dimensional models
• 3+ years of experience building responsive data visualizations using Tableau or equivalent
• Demonstrated experience using the tools of Analytics Engineering such as github, dbt efficiently and effectively
• Demonstrated experience designing, implementing, operating, and extending enterprise dimensional models within Snowflake
• Demonstrated capacity to communicate complex business activities, technical requirements, and recommendations clearly and concisely
• Demonstrated ability to self-manage priorities and workflow
• Demonstrated experience creating and developing partnerships with internal team members towards the delivery of impactful analytics solutions

Preferred (Qualifications/experiences that are preferred for the position)

• Exceptional communication skills, specifically the ability to translate technical requirements into business context and value
• Experience working closely with Data Engineers, Data Scientists, and Machine Learning Engineers to extend the value and impact of analytics solutions
• Experience creating/running using Python or Pyspark jobs within Azure and AWS
• Experience setting up serverless functions using AWS Lambda or Azure functions.