Senior Data Product Accelerator Lead – Data Innovation, Tools

U.S. Bank

Senior Data Product Accelerator Lead driving innovation and tool rationalization within the Enterprise Data Office at U.S. Bank.

Posted 7/4/2026full-timeMinneapolis • Illinois, Minnesota, North Carolina, Texas • 🇺🇸 United StatesSenior💰 $149,515 - $175,900 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud PlatformHadoopPythonSparkSQLTableau

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

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

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Hard Skills & Tools

Data EngineeringAnalytics EngineeringPlatform EnablementETL AutomationBig Data TechnologiesHadoopHiveSparkVisual AnalyticsProgramming Languages

Soft Skills

Organizational SkillsProblem-SolvingProject ManagementCommunication SkillsInfluencing Skills