*****THIS POSITION IS NOT ELIGIBLE FOR VISA SPONSORSHIP*****

What You'll Do:

This position will join OCC's centralized data analytics team to enhance organizational data analytics capabilities through close business partnership, requirements gathering, and solution delivery. The individual will collaborate extensively with the Data Engineering team to architect and develop the internal analytics data layer and maintain supporting ETL processes.

The successful candidate will develop deep expertise in OCC's data models and provide cross-organizational support to maximize data utilization. They will tackle strategic data challenges affecting multiple teams by developing solutions that address immediate needs while anticipating future analytical requirements.

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

Primary Duties and Responsibilities:

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

• Design and maintain OCC analytics solutions drawing from both raw and semantic data layers

• Partner with business units to gather requirements and develop targeted analytics solutions

• Create data models ensuring information availability in the analytics warehouse for analysis and dashboard development

• Help establish Data Analytics standards and collaborate with embedded business analysts to ensure adherence

• Develop comprehensive documentation and testing protocols to guarantee data accuracy and accessibility

• Identify and distribute data and analytics best practices across the team

• Continuously expand knowledge of data and analytics engineering methodologies to enhance infrastructure maintainability and reliability

• Champion self-service capabilities and data literacy among business users through semantic layer utilization, analytics platforms (Tableau, Python), and CI/CD tools

• Pursue ongoing professional development in data analytics, cloud computing, options trading, and financial risk management to improve analytics infrastructure

• Provide guidance to business-embedded data analysts in addressing analytical challenges and support 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 and IT teams -- Data Platform Team, Systems & Infrastructure, Security, DevOps, Networking) to craft solutions that align business goals with internal processes, security, and  delivery standards in mind.

• [Required] Ability to communicate technical concepts to audiences with varying levels of technical background and synthesize 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 (SELECT) SQL queries

• [Required] Ability to write and optimize python for custom data pipeline code (virtual environments, scripts vs. modules vs packages, functional programming, unit testing)

• [Required] Strong Experience with data viz/prep tools (preferably Tableau and Alteryx)

• [Required] Experience with a source code version control repository system, branch management, pull requests (preferably Git)

• [Preferred] Experience with transformation/semantic layer frameworks, such as dbt

• [Preferred] Familiarity with services on at least one cloud computing platform, such as AWS or Azure, or a cloud data platform such as Databricks or Snowflake

• [Preferred] Familiarity with data modeling design concepts such as 3rd-normal form or denormalization modeling concepts such as 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/or Experience:

• [Required] Bachelor's or Master’s degree in a quantitative discipline (e.g., Statistics, Computer Sci