Staff Data Engineer-AI Platform

Responsibilities: Job Summary: As a Staff Data Engineer, you'll lead, coach, and mentor engineers and teams and provide technical direction and support. You'll collaborate with Product, Data Science, Application, and Analytics teams to develop a clear understanding of data and data infrastructure needs to resolve data-related technical issues and ensure optimal data design and efficiency.

Key Responsibilities & Essential Functions:

Design & Development:

Leads team in designing / developing data integrations that support application engineering and system integration

Leads design / development / maintenance of largescale data pipelines; may assist in diagnosing / solving complex production support issues

Provides operational and technical expertise to design algorithms patterns that support large/complex datasets for analytics, implement calculations, cleanse data, ensure standardization of data, and map / link data from more than one source

Leads engineers across one or more squads to deliver initiatives

Mentors / provides support to junior data engineers; coaches / mentors engineers in engineering techniques, processes, new technologies

Builds / supports complex data pipelines, APIs, data integrations, data streaming solutions, and predictive model implementations

Identifies complex data from upstream sources to enable new capabilities

Designs and builds large-scale batch / real-time data pipelines with big data processing frameworks

Architects monitoring capabilities based on business SLA and data quality

Maintains / streamlines existing data pipelines end to end

Performs full SDLC process, including planning, design, development, certification, implementation, and support on more complex projects

Establishes team operational plans; develops / implements new processes, standards, and operational plans that impact results; develops technical roadmaps

Makes recommendations for overall data platforms, work flow, design, architecture, security, scalability, reliability, and performance

Recommends changes to processes, tools at the group / dept level based on industry standards, patterns, and practices

Tests technical solutions to ensure data integrity and system functionality of own work, with consideration toward broader system, E2E

Designs scalable, efficient data models to support data integration, storage, and retrieval across complex systems.

Develops and implements data quality framework for data accuracy, consistency, and completeness across workflows.

Works with Product, Business, and Analyst stakeholders to confirm data quality, discuss requirements, and support data testing

Creates team documentation and training related to technology stacks and standards

Diagnoses / troubleshoots extremely complex issues independently

Performs data validation and quality assurance on own work and of junior engineers

Collaborates with external technical teams to ensure timely, high-quality solutions

Engages with shared services teams and vendors as needed

Influences others in technical decision-making / technology adoption in assigned domain

Knowledge in machine learning concepts

The responsibilities and essential functions outlined above describe the general nature and level of work assigned to this position. This is not an exhaustive list of all duties, responsibilities, and skills required. Duties and responsibilities may be modified at any time based on business needs. Employees may be required to perform other job-related tasks as requested by their supervisor, subject to reasonable accommodations.

Qualifications & Key Requirements:

Work Experience:

of experience related to data engineering -

leadership experience -

Experience in team leadership -

Experience working in large scale infrastructure -

large data sets -

and mission critical SLAs -

Knowledge/Skills/Abilities:

Comprehensive knowledge of Lean Startup / Agile development methodologies -

Knowledge of business intelligence, analytics / reporting, and application integration -

Knowledge of data architectures such as data warehouse, data lake, and data mesh and when to apply -

Expert understanding of coding standards, design principles / patterns, and data architecture and data modeling best practices and guidelines for different data and analytic platforms -

Advanced verbal / written communication and data presentation skills -

Strong prioritization skills -

Ability to deliver on ambiguous projects with incomplete information -

Ability to act as a thought leader and mentor to junior team members -

Ability / willingness to learn new technologies as they emerge -

Ability to calmly work under pressure -

Ability to work a flexible schedule as needed -

Ability to collaborate across multiple work locations -

Ability to work within a team, and willingness to take feedback from peers and mentors -

Education: A related degree or comparable formal training, certification, or work experience -

Licenses/Certifications:

Physical Demands & Working Conditions:

Function in a fast-paced environment

Work extended hours; sit for extended periods

The work environment characteristics described here are representative of those a Partner encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Last revised: 11/01/2024