• Candidates must complete a background check upon offer • The team you will join is a close-knit, cross-functional team with Product Managers, Software Engineers, Program Managers, and Business Intelligence Engineers. You will have the opportunity to learn from other BIEs on our team and partner closely with a Data Engineering team that we work with regularly. We look to move fast while promoting learning. You will be encouraged to learn about and leverage Generative AI/LLMs in your daily work. From day 1, you will be an important member of the team that will have the chance to grow while contributing to high-impact efforts. Key Responsibilities: • Own the design, development, and maintenance of scalable solutions for ongoing metrics, reports, analyses, and dashboards to support drive understanding of the engagement and relevance of customer experiences. • You will create data visualizations, in at least in Excel and Quicksight dashboards, to make data more interpretable and actionable for the business. • Translate business problem statements into reporting/analysis requirements. Work with internal customers, including Product Leaders, Data Engineers, Software Engineers, and other BIEs, to define best output based on expressed stakeholder needs. • Design and create data tables to support ongoing reporting, analyses, and customer experiences. This will include gathering business requirements, designing the schema, building data pipeline, performing data validation, and loading table into required databases. • Perform ad-hoc deep-dive analyses to identify the drivers of changes in key metrics, size new opportunities., explore unusual patterns in the data, and how customers are using a feature. Employ data mining, model building, segmentation, and other analytical techniques to capture important trends in customer segments. • Become an expert in relevant data sources and metrics. Identify and recommend data sources and metric definitions to support business requirements collected from partners and based on your knowledge/expertise. Use your expertise to define and test hypotheses. • Develop tools and mechanisms that enable self-service access to data for business and technical partners. This includes providing clear documentation for your reporting and comments in your code/queries. • Review and audit existing ETL jobs and SQL queries. • Monitor and troubleshoot operational or data issues in the data pipelines. Basic Qualifications • Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field. • 3+ years in analyzing and interpreting data with Redshift, Oracle, NoSQL etc. • 3+ years in designing, building, and automating recurring reporting/dashboards in support of a business, product, or program team. • Expertise in writing complex SQL queries and optimizing them to run efficiently. • Expertise with data reporting and visualization using Excel, Tableau, Quicksight, or similar tools. • Experience with data modeling, warehousing and building ETL pipelines. • Experience performing basic statistical analysis. Preferred Qualifications • Graduate degree in math/statistics, computer science or related field, or marketing is highly desirable • Experience working in e-Commerce or Retail is a plus. • Experience working in a role focused on customer behavior is a plus. • Scripting experience using Python to process data for modeling. • Experience in Statistical Analysis packages such as R, SAS and Matlab • Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift • Experience in designing and implementing Machine Learning solutions. Horizontal facilitates valuable and productive conversations between you and potential employers. We can assist you in growing your career by partnering you with employers that offer challenging assignments. For those that join the team, we offer competitive compensation and benefits including medical, dental, vision, and retirement. Check out all we have to offer and how you can become part of the Horizontal Talent Team. The pay range for this role is $31 - $63 per hour. This is not a guarantee of compensation, as final offer amount may vary based on factors including but not limited to experience and geographic location.