Associate Principal, Data Analytics Engineering

What You'll Do:

This role will be an active contributor to developing business-focused data engineering solutions and enterprise data models for our most important data assets to level up OCC's analytics capabilities. They will become an expert on OCC’s core business data sets to support teams across the organization to successfully harness these data. This role will also work on strategic data challenges, with a strong focus on business user requirements gathering, system design and build of analytics infrastructure, running technology proof-of-concepts, and evolving our production analytics platforms to meet the evolving needs of risk managers, quants, and analytics developers, while aligning to the company’s security and IT standards.

Primary Duties and Responsibilities:

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

• Design and implement cloud infrastructure for internal analytics zone in collaboration with our data architect, OCC’s Data Platform team, DevOps, IT

• Assist in the build, test, and deploy semantic layer’s virtual and physical data models that simplify complex semi-structured data, eliminate multiple definitions of similar data, create query-friendly datasets, and standardize column naming for downstream users that are developing quantitative analytics, dashboards, and internal risk applications.

• Lead the build and implementation for big data processing solutions that meet latency SLAs and access pattern needs of business users who need to analyze the large datasets generated by OCC’s risk models

• Take a lead in implementing DataOps practices of observability and monitoring through automation for semantic layer and other data products to ensure proactive data system failure detection and incident response

• Learn user wants, motivations, priorities, and “the why” as part of eliciting business requirements with developers in risk management departments

• Work with upstream data producers to understand how their systems generate data, and how they are subject to change over time to help anticipate and manage schema drift from semantic layer

• Collaborate with Data Governance, Data Platform Team, and DBAs to design access controls to data platform that meet business and internal governance needs

• Create documentation and testing to ensure data lineage is traceable and semantic layer components are easily discoverable and useful to business users

• Teach self-service capabilities and data literacy with business users leveraging the semantic layer, analytics tools , and CI/CD tools

• Invest in your continued learning of on modern data engineering, cloud computing, options trading industry, and financial risk management, with an eye towards improving maintainability, reliability, and utility of our analytics infrastructure

• Assist risk analysts in solving their analytics questions/challenges and support ad-hoc development with them, as needed.

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] past experience building data products or analytics systems depended on by other users

• [Required] Ability to communicate technical concepts to audiences and ask pressing questions of people with varying levels of technical background, and synthesize non-technical requests into a technical specification

• [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 and DDL queries

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

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

• [Required] Experience working with a linux shell and with container frameworks like docker for portable code distribution and execution

• [Preferred] Experience w