As the Staff Data Architect at Possible, you will be responsible for designing, enhancing, building, and maintaining our data management systems. Critical responsibilities including; review and analyze existing data systems at Possible, including automated data pipelines and data lake in the cloud from a data security and integration perspective, leading the data governance efforts, build and enhance the data management system to support the next phase of growth at Possible. We are looking for a self-starter who can lead and is passionate about data to solve business problems.

This role requires a high level of collaboration and engineering caliber as you work cross-functionally to answer critical strategic questions and drive architecture decisions that will help Possible achieve the growth ahead. This role reports directly to the Head of Data Science and ML.

Responsibilities

• Owning the design, and development of end-to-end data pipelines and workflows
• Engineering solutions to aggregate and automate large-scale data flows from varying sources
• Leading the team on the formation and execution of data governance framework, policies, and standards
• Collaborate with Engineers and Scientists in the organization to construct complex data sources for algorithms and machine learning models
• Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
• Build real-time streaming from internal and external sources to provide insights into the business
• Build, analyze and present actionable data to Marketing/Credit Risk/Finance/Product teams
• Help continually improve ongoing reporting and analysis processes, automating or simplifying customer self-service support
• Design our data models for optimal storage and retrieval and to meet critical product and business requirements
• Understand and influence logging to support our data flow, architecting logging best practices where needed
• Contribute to shared Data Engineering tooling & standards to improve the productivity and quality of output for Data Engineers across the company
• Improve data quality by using & improving internal tools to detect issues automatically

Qualifications & Skills

• 7+ years of experience as a Data Architect or Senior Data Engineer or a similar role
• Bachelor’s and/or Master’s degree, preferably in CS, or equivalent experience
• Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
• Experience with data modeling, data warehousing, and building ETL pipelines
• Knowledge of batch and streaming data architectures
• Experience with AWS technologies including Redshift, RDS, S3, EML, Glue, Athena or similar solutions built around Hive/Spark etc.
• Experience communicating with senior management as well as with colleagues from engineering, analytics, and business backgrounds
• Experience providing technical leadership and mentoring other engineers for best practices on data engineering
• Demonstrated strength in data modeling, ETL development, and data warehousing
• Knowledge of data management fundamentals and data storage principles
• Knowledge of distributed systems as it pertains to data storage and computing
• Proficiency in Python, SQL, or other similar languages.