Senior Data Product Accelerator Lead – Data Innovation, Tools

Role Overview

• Lead the design and evolution of reusable data product accelerators, reference architectures, and integration patterns across platforms such as Snowflake, Databricks, and Power Platform
• Serve as a senior technical and product advisor to delivery teams adopting enterprise data platforms and tools
• Identify recurring friction points in data product delivery and design scalable solutions that remove those barriers
• Partner with platform, architecture, and governance teams to evaluate, test, and validate data and analytics tools
• Lead proofs of concept and comparative assessments to inform tool rationalization and standardization decisions
• Translate platform capabilities into clear adoption pathways, playbooks, and usage guidance for teams
• Apply product thinking to data and analytics capabilities, ensuring solutions are designed for usability, adoption, and measurable impact
• Define success metrics for accelerators and enablement efforts, tracking adoption, reuse, and productivity gains
• Continuously refine assets based on feedback, usage data, and evolving enterprise needs
• Work closely with data engineers, analytics engineers, architects, data product owners, and governance partners to align solutions with enterprise data strategy
• Act as a connector across teams, ensuring consistency while respecting domain specific needs
• Influence engineering and product standards through credibility, hands-on expertise, and demonstrated results
• Evaluating, testing, and experimenting with emerging data and AI tools, platforms, and services
• Documenting project outcomes, transition plans, adoption guides, and solution usage scripts to support enterprise rollout
• This role requires effective project management, communication, and collaboration skills, along with the ability to work effectively with stakeholders across data, technology, and product owner teams

Requirements

• Bachelor’s Degree in a quantitative field such as computer science, engineering, data science, mathematics, or statistics
• 10+ years of experience across data engineering, analytics engineering, platform enablement, or data product roles
• Demonstrated experience influencing adoption of shared platforms, tools, or standards in a large enterprise environment
• Proven track record of designing reusable components or standards adopted by multiple teams
• Experience working across Snowflake, Databricks, and cloud ecosystems (Azure, AWS, or GCP)
• Experience working in regulated or large-scale enterprise environments preferred
• Strong organizational skills with the ability to manage multiple initiatives concurrently
• Deep understanding of banking and financial institution terms
• Knowledge of banking regulation and requirements for regulatory reporting
• Strong analytical, organizational, problem-solving, and project management skills
• Hands-on experience with programming languages such as Python and SQL
• Proficiency with big data technologies including Hadoop, Hive, and Spark
• Expertise in visual analytics tools such as Power BI, Tableau, or equivalent platforms
• Experience with Power Platform tools such as Power Automate and Power Apps
• Proven track record in automating and optimizing ETL processes at scale
• Excellent written and verbal communication skills for documenting technical processes and engaging with cross-functional teams and present to senior management

Tech Stack

• AWS
• Azure
• Cloud
• ETL
• Google Cloud Platform
• Hadoop
• Python
• Spark
• SQL
• Tableau

Benefits

• Healthcare (medical, dental, vision)
• Basic term and optional term life insurance
• Short-term and long-term disability
• Pregnancy disability and parental leave
• 401(k) and employer-funded retirement plan
• Paid vacation (from two to five weeks depending on salary grade and tenure)
• Up to 11 paid holiday opportunities
• Adoption assistance
• Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law