Senior Associate, Data Analytics Engineering

What You'll Do

This position is part of a centralized data analytics team focused on enhancing organizational analytics capabilities through close business partnership, requirements gathering, and solution delivery. The individual will work closely with Data Engineering to architect and develop the internal analytics data layer and maintain supporting ETL processes.

The successful candidate will develop deep expertise in enterprise data models and provide cross-functional support to maximize data utilization. They will address strategic data challenges impacting multiple teams by delivering solutions that meet current needs and anticipate future analytical requirements.

This role involves promoting and enforcing analytics standards while ensuring business teams have appropriate access to data for BI reporting, dashboarding, and ad-hoc analysis.

Primary Duties and Responsibilities

To perform this job successfully, an individual must be able to perform each primary duty satisfactorily:

• Design and maintain analytics solutions using both raw and semantic data layers
• Partner with business units to gather requirements and develop targeted analytics solutions
• Create data models to ensure information availability in the analytics warehouse for analysis and dashboard development
• Help establish analytics standards and collaborate with embedded business analysts to ensure adherence
• Develop comprehensive documentation and testing protocols to ensure data accuracy and accessibility
• Identify and share data and analytics best practices across the team
• Continuously expand knowledge of data and analytics engineering methodologies to improve infrastructure maintainability and reliability
• Champion self-service capabilities and data literacy among business users through semantic layer utilization, analytics platforms (e.g., Tableau, Python), and CI/CD tools
• Pursue ongoing professional development in data analytics, cloud computing, and financial risk management to improve analytics infrastructure
• Provide guidance to business-embedded data analysts in addressing analytical challenges and supporting ad-hoc development needs

Supervisory Responsibilities

None

Qualifications

The requirements listed are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the primary functions.

• [Required] Ability to collaborate with multiple partners (e.g., Business Users, Data and Solution Architects, Data Governance, IT teams, Security, DevOps, Networking) to craft solutions that align business goals with internal processes and delivery standards
• [Required] Ability to communicate technical concepts to audiences with varying levels of technical background and translate non-technical requests into technical output
• [Required] Comfortable supporting business analysts on high-priority projects
• [Required] High attention to detail, tradeoffs, and an ability to think structurally about a solution

Technical Skills

• [Required] Ability to write and optimize complex analytical SQL queries
• [Required] Ability to write and optimize Python for custom data pipeline code (e.g., virtual environments, scripts vs. modules vs. packages, functional programming, unit testing)
• [Required] Strong experience with data visualization/preparation tools (preferably Tableau and Alteryx)
• [Required] Experience with source code version control systems, branch management, and pull requests (preferably Git)
• [Preferred] Experience with transformation/semantic layer frameworks such as dbt
• [Preferred] Familiarity with cloud computing platforms (e.g., AWS, Azure) or cloud data platforms (e.g., Databricks, Snowflake)
• [Preferred] Familiarity with data modeling design concepts such as 3rd-normal form or star-schema
• [Preferred] Exposure to batch orchestration tools such as Apache Airflow, Dagster, or Prefect
• [Preferred] Understanding of applied statistics and hands-on experience applying these concepts

Education and Experience

• [Required] Bachelor's or Master's degree in a quantitative discipline (e.g., Statistics, Computer Science, Mathematics, Physics, Data Science, Electrical Engineering, Information Systems) or equivalent professional experience
• [Required] 3+ years of experience as a data analyst, data engineer, software engineer, data scientist, financial risk analyst, or business intelligence analyst

Certificates or Licenses

• [Preferred] BI tool certification
• [Preferred] Financial Analyst certification