Job Description
The Technical Analyst 3 partners closely with stakeholders to understand business and technical needs and translate them into actionable requirements, solution documentation, and delivery plans that support technology initiatives and operational outcomes.
This role owns defined technical analysis workstreams end-to-end, evaluates systems, processes, data flows, risks, and dependencies, and supports the delivery of reliable solutions across product, engineering, operations, data, and technology partners.
Success in this role requires strong technical execution, structured problem solving, clear communication, disciplined documentation, and the ability to connect technical recommendations to measurable business value, stakeholder outcomes, and enterprise standards.
Applies GenAI tools to quickly orient to and contribute across new work within the supported business unit. The role uses approved AI tools to accelerate research, requirements synthesis, documentation, analysis, and workflow efficiency while validating outputs, applying sound judgment, and ensuring alignment with governance expectations.
The position emphasizes reusable documentation, stakeholder alignment, risk management, and governance to ensure technical solutions are feasible, scalable, supportable, and delivery-ready.
Essential Job Skills/Duties
• Support end-to-end delivery of features, from intake and grooming through development and implementation, providing ongoing visibility into progress, data validation, production support, and confirming that requirements and expectations are fully met.
• Develop, validate, and maintain technical requirements, solution analyses, implementation approaches, clear technical summaries, risk assessments, and governance artifacts.
• Collaborate with product, engineering, operations, data, security, and technology stakeholders to align technical work with business priorities under leadership oversight.
• For well-defined enhancements, develop code to modify gold-layer data assets in accordance with established review and deployment standards.
• Proactively manage moderate ambiguity within defined workstreams and resolve blockers with the assigned leader to maintain momentum.
• Design, develop, and maintain scalable data pipelines using Databricks and AWS-native services, leveraging AI to accelerate development and reduce manual effort.
• Perform data validation and reconciliation across multiple systems using SQL and distributed query tools (e.g., Presto), incorporating AI to improve speed and accuracy.
• Partner with data engineering teams to optimize performance, scalability, and cost efficiency in cloud environments, using AI-assisted insights to inform decisions.
• Approach daily tasks with an AI-first mindset and use approved tools such as Cursor, ChatGPT, and Claude across research, analysis, synthesis, documentation, and workflow acceleration, while validating outputs and applying sound judgment.
Required Technical Skills
• Business Acumen: Invest in understanding the supported business unit's operations to enable requirements gathering, anticipate needs, and connect technical recommendations to defined business objectives, KPIs, and decision points.
• Advanced SQL & Query Optimization: Write, tune, and validate complex SQL queries across large-scale datasets, leveraging AI-assisted tools to accelerate development, debugging, and performance optimization.
• Storytelling: Craft narratives that link technical analysis, system impacts, risks, and recommendations to business value and actionable next steps.
• Data Modeling: In partnership with data and engineering teams, evaluate reliable, scalable data structures and system dependencies that support repeatable analysis, reporting, and solution delivery.
• Metadata Management: Maintain metadata, requirements, process, and system documentation standards to support traceable, reproducible, and supportable technology analysis.
• Technical Governance: Follow documentation, validation, risk management, and governance/change management standards for scalable technology delivery.
• Technical Delivery Leadership: Lead product and engineering team efforts using SDLC methodologies including Agile, Scrum, Kanban, and Hybrid to support effective planning, prioritization, delivery, and implementation.
• Technical Delivery Leadership: Lead product and engineering team efforts using SDLC methodologies including Agile, Scrum, Kanban, and Hybrid to support effective planning, prioritization, delivery, and implementation.
• Cloud Data Platforms (AWS): Work within AWS environments to support scalable data ingestion, transformation, and access patterns, using AI to improve efficiency in design and troubleshooting.
• Distributed Query Engines (Presto/Trino): Utilize Presto to efficiently query distributed datasets, incorporating AI-driven approaches to accelerate analysis, validation, and issue resolution.
• Databricks & Spark Ecosystem: Develop and support data workflows in Databricks using Spark (PySpark/SQL), including Delta Lake and notebook-based development, while leveraging AI to streamline coding, testing, and documentation.
• AI-Accelerated Development: Consistently apply approved GenAI tools (e.g., ChatGPT, Claude, Cursor) to enhance productivity across querying, data analysis, documentation, and technical problem solving, while validating outputs and ensuring alignment with governance standards.
• Understand where human judgment, peer consultation, governance, and cross-functional decision-making remain essential.
Required Soft/Leadership Skills
• Communicate complex technical concepts clearly to technical and non-technical audiences and adjust technical depth for the audience as needed.
• Frame problems, ask strong questions, identify gaps, and structure technical approaches effectively.
• Build strong cross-functional partnerships and manage stakeholder expectations proactively across product, engineering, operations, data, and business teams.
• Prioritize competing technical requests and deliver against deadlines with leader guidance and oversight.
• Operate effectively within ambiguity, anticipate technical challenges, and adapt as requirements evolve.
• Maintain high standards of quality, integrity, ownership, accountability, and follow-through.
• Contribute to team effectiveness through knowledge sharing, collaboration, informal mentoring, and practical delivery guidance.
Required Education and Experience
• Bachelor's degree in Data Science, Computer Science, Management Information Systems, Engineering, or a related field.
• 4-6 years of experience in a similar role with a proven track record of increasing responsibility and demonstrated success.
Travel Requirements
• Occasional local and overnight travel for meetings or workshops.
• Up to 10 percent travel.
Physical Demands and Working Conditions
• On-site attendance required a minimum of 3 days per week.
• Frequently stationary.
• 20/20 corrected vision.
• Ability to receive detailed information if spoken to