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

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

Last revised: 11/01/2024

JDENGINEERING