The Role

As a Principal Data Analytics Engineer at Stori you will leverage your analytics and engineering skills along with cutting edge big data technology to innovate, design, build, and maintain well-managed data products to solve complex business problems. This role will be responsible for leading the development of high quality, monitored and documented data products that will enable advanced analytics used for the decision making of several business analysts and business leaders.

• Bachelor degree in Computer Science, Software Engineering or equivalent work experience
• 5+ years of experience working as a Data Analytics Engineer or Data Engineer building highly scalable data products
• Proven experience using SQL and Python
• Experience with data processing technologies (i.e.: DBT, Spark, Pandas), orchestration solutions (ie: Airflow, Prefect) and reporting tools (i.e. Quicksight, Looker )
• Experience working with Cloud Providers, ideally AWS.
• Experience leading small teams (1 to 3 people) of Data Engineers and/or Data Analytics Engineers
• Strong planning and organizational skills
• Advanced written and spoken communication skills in English
• Past experience in the financial sector is desirable but not required
• Be responsible for designing, developing and maintaining data products used to unlock analytics capabilities to the business.
• Interact with business analysts and other stakeholders to gather new data product requirements, break them down into concrete deliverables, estimate development effort and prioritize among other initiatives based on their impact.
• Track the progress of planned initiatives, identifying, solving and communicating risks and blockers that could impact on the delivery due dates.
• Identify, estimate and prioritize technical initiatives that help to improve the maintainability, stability and quality of the data products.
• Develop critical features and implement engineering best practices throughout the lifecycle of data products to improve the quality of the deliverables.
• Interact with other technical teams like Data Infrastructure, Data Governance, DevOps, Security to adhere their solution and policies to the data products as well as suggest improvements.
• Lead, hire and retain new talent in the team