Data/AI Engineer III (US)

The Data/AI Engineer III will deliver highly complex data engineering capabilities spanning data modeling, ingestion (ETL), quality/profiling, metadata, and lineage. This role also supports design and development efforts aligned to business and technical requirements, including work that enables GenAI and AI/ML workloads.

Role Overview

This position provides broad data engineering functions, including data acquisition and ingestion, metadata enrichment and management, and provenance and data lineage. The engineer designs and develops solutions, analyzes and adapts technical approaches, and executes end-to-end development activities such as coding, testing, debugging, and deployment coordination. The role functions as a primary subject matter expert in multiple areas related to core accountabilities and consults across teams on research, analysis, design, and support.

Key Responsibilities

• Provide data engineering functions including data modeling, data quality, data profiling, data acquisition and ingestion, ETL, metadata enrichment and management, and data provenance and lineage.
• Perform highly complex technical tasks independently and use established patterns to address complex problems, leading development of new patterns when required.
• Design and develop solutions that meet business and technical requirements, including analysis, integration, coding, testing, debugging, and execution.
• Serve as a recognized subject matter expert across multiple areas directly and indirectly related to key accountabilities.
• Consult with peers and partners across multiple teams on research, analysis, design, and support activities.
• Conduct data analysis to assess data management requirements for a Platform or Journey, including complex analysis involving multiple pods or products.
• Maintain expert knowledge of upstream data through profiling, quality reporting, and metadata production.
• Support acquisition and ingestion of data and develop data models using industry standard modeling tools.
• Develop and maintain complex ETL jobs and frameworks using the Bank’s standard tools.
• Articulate complex, large scale, and high impact technical design and development details to non-technical business partners.
• Elicit and analyze business and data requirements to develop complete business solutions, including entity relationship diagrams, dimensional data models, ETL and business rules, data lifecycle management, governance, lineage, and metadata.
• Ensure data is maintained in compliance with enterprise data standards, policies, and guidelines.
• Capture and ensure metadata and data lineage are compatible with enterprise metadata and data management tools and processes.
• Support QA through data analysis and investigations for complex issues and test cases as part of SIT/UAT/PAT testing.
• Provide escalation support on complex data issues and participate in post-implementation oversight during the warranty period.
• Execute source code management activities, including code check-in/check-out into the source code repository, and support packaging and deployment with ITS/ARE teams via CI and CD.
• Lead participation in design and architecture reviews and support release management by raising ServiceNow requests and working with the change management team.
• Coordinate with technology work teams (including ITS, ARE, Architecture, Enterprise Protect) to help ensure delivery success.
• Adhere to internal policies/procedures and applicable regulatory guidelines; contribute to standard security coding practices to reduce common coding vulnerabilities.
• Identify and document technical decisions, technical risks, and lessons learned, implementing enhancements accordingly; manage risks and escalate non-standard, high-risk activities when necessary.
• Enable and mentor team members through knowledge sharing and engineering best practices, and support a collaborative environment through timely communication.
• Act as a brand ambassador for the business area/function and the bank, internally and/or externally.

Required Qualifications

• Degree, Postgraduate Degree, or Technical Certificate in Data Management or a related discipline (e.g., Computer Science, Engineering), or equivalent practical experience.
• Graduate Degree preferred.
• 5+ years of relevant experience.
• 5+ years of experience with strong hands-on data engineering using Azure and Databricks.
• 5+ years of experience with advanced Python, SQL, Spark/PySpark.
• Understanding of batch, streaming, dimensional modeling, Lakehouse architecture, and distributed processing.
• Hands-on experience developing GenAI or agentic applications.
• Experience with Databricks Genie, AI/BI, MLflow, vector search, RAG, or comparable technologies.
• Experience engineering data for AI/ML workloads.
• Experience within financial services or another highly regulated industry.

Technologies

• Azure, Databricks
• Python, SQL, Spark, PySpark
• GenAI, agentic applications
• Databricks Genie, AI/BI, MLflow
• Vector search, RAG
• Lakehouse architecture
• CI & CD
• ServiceNow
• SIT/UAT/PAT
• ETL, data lineage, dimensional modeling, entity relationship diagrams

Compensation and Benefits

• Base salary: USD 98,160 - 159,270 per yearly
• Health and well-being benefits
• Savings and retirement programs
• Paid time off (Vacation PTO, Flex PTO, Holiday PTO)
• Banking benefits and discounts
• Career development
• Base salary and variable compensation/incentive awards (eligibility for cash and/or equity incentive awards, generally through participation in an incentive plan)

Work Location and Schedule

• Location: Mount Laurel, New Jersey, United States of America
• Work mode: Onsite
• Hours: 40

Travel and Physical Requirements

• Domestic travel: Occasional
• International travel: Never
• Performing sedentary work: Continuous
• Performing multiple tasks: Continuous
• Operating standard office equipment: Continuous
• Responding quickly to sounds: Occasional
• Sitting: Continuous
• Standing: Occasional
• Walking: Occasional
• Moving safely in confined spaces: Occasional
• Lifting/Carrying (under 25 lbs.): Occasional
• Lifting/Carrying (over 25 lbs.): Never
• Squatting: Occasional
• Bending: Occasional
• Kneeling: Never
• Crawling: Never
• Climbing: Never
• Reaching overhead: Never
• Reaching forward: Occasional
• Pushing/ Pulling/ Twisting: Never
• Concentrating for long periods of time: Continuous
• Applying common sense to deal with standardized situations: Continuous
• Reading, writing and comprehending instructions: Continuous
• Adding, subtracting, multiplying and dividing: Continuous

Line of Business

• Technology Solutions