Sr. Data Product Manager (Data Governance & Investment Banking)
New York City NY
Need local resumes with candidates open for Client In-Person interview.
Domain: Data Governance & Investment Banking experience is MUST.
Overview:
- We are seeking an experienced **Data Product Manager** with a robust background in Data Engineering and a deep understanding of banking and financial services data.
- The ideal candidate will play a pivotal role in defining developing and managing data products and solutions working collaboratively with Data Engineers Data Analysts Data Scientists and Business Stakeholders.
- The candidate will leverage their technical expertise to ensure our data offerings are robust scalable and aligned with business needs and compliance standards.
Key Responsibilities:
Product Ownership & Strategy:
- Define and prioritize data products features and roadmaps aligned with banking operations and analytics requirements.
- Develop a comprehensive understanding of business needs related to data translating these into actionable product requirements.
- Collaborate with stakeholders to gather refine and document data requirements ensuring alignment with organizational goals.
Cross-Functional Collaboration::
- Work closely with Data Engineers to design develop and enhance scalable data pipelines ensuring they meet quality and performance standards.
- Coordinate with Data Analysts and Data Scientists to facilitate data access usability and analytics.
- Act as a liaison between technical teams and business units to facilitate clear communication and understanding.
Data Governance & Compliance:
- Ensure all data products are developed and maintained in compliance with banking industry data security privacy and governance standards.
- Define and implement policies for data quality integrity and security.
Data Lifecycle & Release Management:
- Oversee the end-to-end lifecycle of data products from development and testing to deployment and monitoring.
- Manage release schedules coordinate deployment activities and ensure robust version control.
- Implement processes for continuous improvement and automation of data workflows.
Technical Oversight & Knowledge:
- Maintain strong understanding of Data Engineering processes including data warehousing ETL/ELT workflows and cloud platforms like Snowflake Azure and Databricks.
- Provide technical guidance and support to Data Engineers on best practices in data architecture pipelines and security standards.
- Stay updated on latest industry trends tools and best practices integrating them into the data product roadmap.
Performance Monitoring & Optimization:
- Monitor data product performance troubleshoot issues and collaborate with engineering teams for tuning and optimization.
- Collect feedback from users to iterate and improve data solutions.
Documentation & Training:
- Maintain clear documentation of data products architecture and processes.
- Conduct training sessions or workshops to facilitate effective utilization of data assets among stakeholders.
Required Skills & Experience:
- Proven experience as a Data Product Manager or similar role with a strong technical background in Data Engineering.
- Deep understanding of Snowflake Python Pyspark SQL and cloud data platforms.
- Extensive experience with data warehousing ETL/ELT processes and data pipeline management.
- Strong knowledge of banking and financial industry data including compliance security and privacy standards.
- Able to bridge the technical and business worlds translating complex data concepts into understandable solutions.
- Familiar with release management CI/CD practices and version control.
- Excellent communication stakeholder management and collaboration skills.
- Experience working with Data Engineers Data Analysts and Business Stakeholders in a fast-paced environment.
Preferred Qualifications:
- Experience working with Azure Databricks and related cloud services.
- Knowledge of streaming technologies like Apache Kafka.
- Familiarity with DevOps practices CI/CD pipelines and Agile methodologies.
- Prior experience in the banking or financial services industries.
Sr. Data Product Manager (Data Governance & Investment Banking) New York City NY Need local resumes with candidates open for Client In-Person interview. Domain: Data Governance & Investment Banking experience is MUST. Overview: We are seeking an experienced **Data Product Manager** with a robust ...
Sr. Data Product Manager (Data Governance & Investment Banking)
New York City NY
Need local resumes with candidates open for Client In-Person interview.
Domain: Data Governance & Investment Banking experience is MUST.
Overview:
- We are seeking an experienced **Data Product Manager** with a robust background in Data Engineering and a deep understanding of banking and financial services data.
- The ideal candidate will play a pivotal role in defining developing and managing data products and solutions working collaboratively with Data Engineers Data Analysts Data Scientists and Business Stakeholders.
- The candidate will leverage their technical expertise to ensure our data offerings are robust scalable and aligned with business needs and compliance standards.
Key Responsibilities:
Product Ownership & Strategy:
- Define and prioritize data products features and roadmaps aligned with banking operations and analytics requirements.
- Develop a comprehensive understanding of business needs related to data translating these into actionable product requirements.
- Collaborate with stakeholders to gather refine and document data requirements ensuring alignment with organizational goals.
Cross-Functional Collaboration::
- Work closely with Data Engineers to design develop and enhance scalable data pipelines ensuring they meet quality and performance standards.
- Coordinate with Data Analysts and Data Scientists to facilitate data access usability and analytics.
- Act as a liaison between technical teams and business units to facilitate clear communication and understanding.
Data Governance & Compliance:
- Ensure all data products are developed and maintained in compliance with banking industry data security privacy and governance standards.
- Define and implement policies for data quality integrity and security.
Data Lifecycle & Release Management:
- Oversee the end-to-end lifecycle of data products from development and testing to deployment and monitoring.
- Manage release schedules coordinate deployment activities and ensure robust version control.
- Implement processes for continuous improvement and automation of data workflows.
Technical Oversight & Knowledge:
- Maintain strong understanding of Data Engineering processes including data warehousing ETL/ELT workflows and cloud platforms like Snowflake Azure and Databricks.
- Provide technical guidance and support to Data Engineers on best practices in data architecture pipelines and security standards.
- Stay updated on latest industry trends tools and best practices integrating them into the data product roadmap.
Performance Monitoring & Optimization:
- Monitor data product performance troubleshoot issues and collaborate with engineering teams for tuning and optimization.
- Collect feedback from users to iterate and improve data solutions.
Documentation & Training:
- Maintain clear documentation of data products architecture and processes.
- Conduct training sessions or workshops to facilitate effective utilization of data assets among stakeholders.
Required Skills & Experience:
- Proven experience as a Data Product Manager or similar role with a strong technical background in Data Engineering.
- Deep understanding of Snowflake Python Pyspark SQL and cloud data platforms.
- Extensive experience with data warehousing ETL/ELT processes and data pipeline management.
- Strong knowledge of banking and financial industry data including compliance security and privacy standards.
- Able to bridge the technical and business worlds translating complex data concepts into understandable solutions.
- Familiar with release management CI/CD practices and version control.
- Excellent communication stakeholder management and collaboration skills.
- Experience working with Data Engineers Data Analysts and Business Stakeholders in a fast-paced environment.
Preferred Qualifications:
- Experience working with Azure Databricks and related cloud services.
- Knowledge of streaming technologies like Apache Kafka.
- Familiarity with DevOps practices CI/CD pipelines and Agile methodologies.
- Prior experience in the banking or financial services industries.
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