What You’ll Bring to The Team:

Florence is seeking an experienced Sr. Data Engineer to design and maintain data pipelines that power analytics and advanced reporting on the Florence Enterprise Data Platform. As a member of the R&D organization you will manage critical business data assets, leveraging cloud based big data tools to enable data-driven decisions across Florence. You will bring a healthy obsession for data quality and a willingness to partner with security and compliance experts, understanding the unique data sovereignty requirements of a global customer base. At Florence, voices are heard, and individuals are respected, and we expect you to ask questions, be curious, and share your story.

You will:

• Craft and build reusable components, frameworks and libraries at scale to support analytics products
• Utilize AI to ensure solutions are efficient and incorporate ai into daily tasks
• Recommend tools and techniques for efficient data movement, transformation, and storage to facilitate a high-performance data warehouse environment
• Design, build, and deploy scalable data pipelines to power analytics and reporting on data elements found across multiple source systems
• Deliver data platform infrastructure as code, managing deployment and configuration requirements as well as internal release documentation
• Identify and address issues concerning data management to improve data quality
• Contribute to our culture, invent new ways to address industry needs, criticize constructively, and help create a world-changing company
• Design and implement redundant systems, policies, and procedures for disaster recovery and data archiving to ensure effective availability, protection, and integrity of data assets.
• Plan and implement capacity and resource expansion to ensure data warehouse scalability
• Work with a collaborative team to identify, create, and deliver reports according to requirements
• Contribute to design and development of data warehouse improvement and growth projects
• Monitor system details within the data warehouse, including stored procedures and execution time, and implement efficiency improvements.
• Ensure security and privacy techniques are applied appropriately to data
• Collaboratively review design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards
• Coach and Train other engineers on engineering best practices
• Troubleshoot data issues and perform root cause analysis to proactively resolve product and operational issues
• Create, update, and maintain system documentation

An Ideal Candidate is/has:

• A bachelor’s or master’s degree in computer science, data science, information science or related field, or equivalent work experience
• 3+ years of experience working with cloud based enterprise analytics platform and/or data warehouse projects (Snowflake preferred)
• 7+ years of experience with SQL on multiple database platforms
• Programming background with experience in data science focused languages such as Python, Scala, R
• Solid understanding of both relational and NoSQL database modeling and schema design principles
• Experience manipulating large datasets and creating high-performance queries
• Experience with large scale data migrations
• Intense focus on data security best practices
• Exercises documentation best practices and proficient with Git
• Ability to thrive in a hybrid work environment
• Positive and action-oriented mindset
• Great interpersonal and communication skills and know how to ask the right questions
• Self-motivated and self-managing, with task organizational skills
• Demonstrated capacity to clearly and concisely communicate complex business activities, technical requirements, and recommendations
• Proficiency in SQL & NoSQL databases (Snowflake, MongoDB), specifically on the development or reporting side
• Collaborate with project managers and business unit leaders for all projects involving data
• Strong understanding of relational data structures, theories, principles, and practices
• Mentor and train other developers and engineers on data engineering best practices and techniques
• Review and provide feedback on other developers code
• Strong knowledge of applicable data privacy practices and laws
• Strong SQL and Schema Comprehension Skills (Many-to-many relationships)
• strong comprehension and experience of data structures
• Strong communication skills with ability to train others

Bonus Points if you have:

• Experience with Snowflake, DBT, Fivetran, Tableau, Postgres, Mongo
• Prior knowledge and exposure to distributed data frameworks
• Proficiency in building modular applications
• Experience with Microservices and/or Service-Oriented Architecture
• Experience with database management and data ops