Job Description:

As the Analytics Engineer you’ll be helping to provide our customers with proactive and actionable reporting on their business goals and activity. You’ll ensure that key business activities are being properly measured and help analyze and explain what the data might mean. The analytics associate will regularly deliver reports, dashboards, and analyses that help our customers to make business decisions. 

The Analytics Engineer will be responsible for both the sustainable delivery of reporting and to help support our customers’ data infrastructure. They should be also looking for opportunities to improve our tools and processes on an ongoing basis, as well as to share analytics best practices with other team members.

Key Responsibilities:

• Delivery of reporting
• Hands-on creation of ad hoc reports, scheduled reports, and dashboards
• Ongoing review and analysis of data as it is delivered
• Synthesis of reporting across channels into meaningful analysis
• Data Visualization
• Help determine the best way to display data so that it is useful and impactful for our customers
• Create presentations of key data points which tell insightful stories
• Comply with reporting standards and practices as outlined by analytics and dev leadership
• Data Presentation
• Able to lead team members and clients through data stories in a compelling, intelligible way
• Build stories and decks to support discussions and business decision making
• Implementation Expertise
• Tagging
• Need to be able to review tag implementations for accuracy
• Should be able to tag but not expected to be the primary resource for this
• Should be able to design tagging scheme that is extensible, thorough, and functional
• Testing
• Work with QA to ensure the thorough testing of all implementations and accuracy of data
• Training
• Share learnings on key analytics concepts, practices, and processes to other team members, and clients as needed
• Help create analytics training materials for guided study or exploration by internal team members

Your knowledge should include these types of platforms:

• Ability to use and to train others on key analytics platforms:
• Analytics Platforms: Google Analytics, Segment, Adobe Analytics
• Tag Managers: Google Tag Manager, Ensighten, Adobe Tag Manager
• Data Platforms: SQL database(s): Postgres, MySQL, Oracle
• Data Warehouses: Google BigQuery, Amazon Redshift, Snowflake
• Dashboard Tools: Tableau, Google Data Studio, Amazon QuickSight
• Heat mapping: Crazy Egg, Lucky Orange, etc.
• Optimization: Optimizely, Adobe Target, Google Optimize, etc.
• Data Analysis/Science: Python data science stack (numpy, pandas, matplotlib, Jupyter) a plus
• Languages: SQL, Javascript, Python