Responsibilities

The Staff Analytics Engineer role is responsible for helping to bridge the gap between business and technology, implementing data solutions to support Treasury, Capital Markets and Finance stakeholders with data-related technical implementations while supporting their data infrastructure needs.

• Serve as the Directly Responsible Individual for major sections of the Enterprise Dimensional Model related to Treasury and Capital Markets
• Design, develop, and extend code to extend the Enterprise Dimensional Model
• Create and maintain architecture and systems documentation
• Maintain the Data Catalog, a scalable resource to support Self-Service and Single-source-of-truth analytics
• Craft code that meets our internal standards for style, maintainability, and best practices for a high-scale database environment. Maintain and advocate for these standards through code review.
• Help promote data innovation across the analytic data environment with a willingness to experiment and to confront hard and complex problems
• Build trust in all interactions and with Trusted Data Development
• Identify and resolve impediments to efficiency and enable the entire Data Program to iterate faster
• Review and improve the data system as a whole, inclusive of data model designs, process flows, and end use cases
• Research new data engineering and analytics methodologies with minimal guidance and support from other team members
• Organize and Plan multi-quarter initiatives and develop the Enterprise Model Roadmap

Qualifications

• Bachelor’s Degree in computer science or equivalent data experience in a financial services environment
• 6 to 8 years of experience with data development and at least 3 years in Analytics Engineering
• 4+ years experience designing, implementing, operating, and extending enterprise dimensional models
• 4+ years working with a large-scale (1B+ Rows) Data Warehouse, preferably in a cloud environment
• 1+ years experience building reports and dashboards in a data visualization tool
• Experience with big data tools (Databricks, Py Spark, Fivtrans), ETL Tools like Talend and DBT, relational SQL including Postgres and MySQL and with data pipeline and workflow mgmt. tools: Jenkins, Harness, Airflow; AWS cloud services: S3, EC2, EMR, RDS and Data Lake, object-oriented/object function scripting languages (Python)
• Demonstrated capacity to communicate complex business activities, technical requirements, and recommendations clearly and concisely
• Demonstrated experience with one or more of the following business subject areas: finance, treasury, capital markets, marketing
• Positive and solution-oriented mindset
• Comfort working in a highly agile, intensely iterative environment
• Self-motivated and self-managing, with task organizational skills
• Demonstrated experience leading 2 or more multi-department analytics projects from inception to operationalization
• Demonstrated proficiency with data system design, including databases, schema, marts, aggregates, and views
• Experience introducing a new tool or technique to a multi-person team, leading to measurable productivity improvement
• Experience with data access and security techniques, both inside and outside of a data warehouse