HAN Staffing

Product Data Manager

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Product Data Manager in NYC, NY, on a full-time contract. Requires strong banking or financial services experience, expertise in data governance and analytics, proficiency in SQL, and familiarity with cloud platforms.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 8, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Fixed Term
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🔒 - Security
Unknown
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📍 - Location detailed
New York City Metropolitan Area
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🧠 - Skills detailed
#BI (Business Intelligence) #AWS (Amazon Web Services) #Data Lineage #Data Architecture #"ETL (Extract #Transform #Load)" #Data Integration #Data Lake #Tableau #Compliance #Cloud #ML (Machine Learning) #Agile #GCP (Google Cloud Platform) #Data Management #Leadership #Security #Big Data #SQL (Structured Query Language) #Stories #Scrum #Scala #Azure #Automation #Looker #Visualization #Data Quality #AI (Artificial Intelligence) #Microsoft Power BI #Data Governance #Data Engineering #Metadata #Strategy
Role description
Hi Associates, I hope you are doing well. We are actively working on an urgent requirement with one of our key clients and believe your background could be a strong fit. Please share your updated resume in word format (.doc/.docx), along with your contact number and your availability for a quick discussion. This is a time-sensitive opportunity, and we are moving quickly with submissions. I would appreciate your prompt response so we can discuss the role in detail. Looking forward to hearing from you soon. Job Title: Data Product Manager Location: NYC, NY (5 days Onsite Role) Job Type - FTC/FTE Key Skills – Data Product Manager: • Strong experience in Data Product Management within Banking or Financial Services environments. • Expertise in defining product vision, roadmap, and strategy for enterprise data platforms and analytics solutions. • Hands-on experience with Data Governance, Data Quality, Metadata Management, and Data Lineage concepts. • Strong understanding of Banking data domains such as Payments, Risk, Compliance, Fraud, Treasury, Customer Data, or Capital Markets. • Experience working with Big Data technologies, Cloud platforms (AWS/Azure/GCP), Data Lakes, and Data Warehousing solutions. • Proficiency in SQL and familiarity with data engineering and ETL processes. • Experience with Agile/Scrum methodologies, backlog management, sprint planning, and stakeholder communication. • Ability to translate business requirements into technical data solutions and product features. • Strong analytical, problem-solving, and stakeholder management skills. • Experience working with BI and visualization tools such as Tableau, Power BI, or Looker. • Knowledge of AI/ML-driven data products and automation solutions is an added advantage. • Familiarity with regulatory and compliance standards in banking environments. Key Responsibilities: • Define and manage the roadmap for enterprise data products aligned with business and regulatory requirements. • Collaborate with business stakeholders, engineering teams, data architects, and analysts to deliver scalable data solutions. • Gather, analyze, and prioritize product requirements and convert them into user stories and functional specifications. • Drive development and implementation of data platforms, dashboards, APIs, and analytics capabilities. • Ensure data quality, governance, security, and compliance standards are maintained across platforms. • Work closely with Data Engineering teams on ETL pipelines, data integrations, and cloud-based data initiatives. • Monitor product performance, KPIs, and adoption metrics to drive continuous improvements. • Lead Agile ceremonies including sprint planning, backlog grooming, and stakeholder demos. • Coordinate cross-functional teams to ensure timely delivery of data initiatives and product releases. • Support business intelligence, reporting, and advanced analytics initiatives for decision-making. • Identify opportunities for automation, optimization, and innovation within data management processes. • Communicate product updates, risks, and strategic initiatives to leadership and executive stakeholders.