Stori's Analytics Engineering team's primary objective is to build easy-to-use, trustworthy, and reliable data products to serve the analytical needs across different product and business functions. You’ll unblock analysis and operational reporting by shaping upstream data into clean, governed, and observable datasets.

Analytics Engineer in Stori solve problems that get in the way of doing analysis. In this role, you are essential to our data strategy in reducing burdens associated with our data models and analytical tools and platforms. You will help business partners to diagnose what is getting in the way of efficient analytics today. Identifying and addressing the root causes will allow Stori to make quick, data informed decisions by removing bottlenecks and automating each stage of the data ops lifecycle. One day, this might mean modeling our upstream data in a better way. The next day, it might mean onboarding a new analytics tool. It can also mean working with source data teams to map out the right data structure to get to a single source of truth on vital business constructs. Our data analysts are critical to our analytics success because they enable our business analysts and data scientists to answer business questions using our data.

• A bachelor degree or foreign equivalent in Computer Science, Mathematics, Information System, Statistics, Economics or related quantitative field.

• English Fluent/proficient.

• A professional with at least 2 years of experience with Data Analytics.

• Preferably 2+ years of Python development experience.

• Preferably 2+ years of SQL knowledge (including the experience of writing queries) and experience with relational databases.

• Preferably Payments/fintech experience.

• Experience with modern reporting and data visualization tools (QuickSight, Tableau, Looker, etc.)

• Strong analytical skills with the ability to collect, organize and analyze significant amounts of information with attention to detail and accuracy.

• Technical expertise in data models, database utilization, data mining, and segmentation techniques.

• Good presentation and communication skills, ability to explain complex technical problems in simple words.

• Assist in the design of appropriate metrics for tracking business objectives, as well as in the creation of a Single Source of Truth for these KPIs.

• Develop reporting related to the area's KPIs, as well as ad-hoc analyses on business and product developments.

• Design and develop the batch data transformation pipelines to merge and transform large raw datasets to analytical datasets that users can quickly derive the insights from.

• Work with product and tech teams to understand the business pipeline, review new products and identify related data sources to provide prescriptive analysis.

• Perform the data validation on complex business logic, and reconciliation across different data sources.

• Identify, understand, analyze, and interpret trends, patterns or gaps in complex data sets.

• Perform data quality monitoring to maintain and assure data and processes integrity.

• Develop the data dictionary and training to educate the business partners on how to best use and interpret the data.

• Solve data issues and perform root cause analysis to proactively resolve product and operational issues.