Data Integration Operations Manager (VP Level)

Shulman Fleming & Partners

Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7-10 years of data integration and operations experience
  • Strong incident management skills within banking frameworks
  • Ability to manage batch processing and SQL Server environments
  • Proficient in SQL and Python development
  • Experience with data integration tools such as Databricks and Azure
  • Excellent communication skills for stakeholder engagement
  • Knowledge of financial products including fixed income and derivatives

Responsibilities

  • Own end-to-end data integration operations and batch workflows
  • Ensure timely execution of integration processes during business hours
  • Monitor SLAs and OLAs for multiple systems
  • Manage production support and incident resolution
  • Drive improvements in integration processes and operational controls
  • Coordinate cross-functional teams for effective delivery
  • Oversee operational risk and compliance adherence

Benefits

  • Hybrid work schedule with local requirement in Iselin, NJ
  • Opportunity to lead critical data operations
  • Engagement with cross-functional teams
  • Potential for career growth in financial services sector
  • Access to cutting-edge integration tools and platforms
Full Job Description
Data Integration Operations Manager (VP Level)

MUST be local to Iselin NJ, Hybrid Schedule

Salary up to $170k

No Sponsorship Available, No Third Party Resumes

In this role you will be accountable for end-to-end data integration operations. You will ensure seamless system connectivity and data integrity across critical data flows. You will own operational execution for their Central Database and strategic DEAL Integration points covering Markets and related Service of Records. Additionally, you will provide oversight of batch workflows and integration processes, and partner with stakeholders to drive operational efficiency and reliability.

Key Responsibilities
  • Own end to end data integration operations, including batch workflows and pipeline.
  • Ensure timely, accurate execution of critical business hour integration processes
  • Monitor and uphold SLAs/OLAs across multiple systems of record
  • Manage production support, incident resolution, and operational risk
  • Drive continuous improvement of integration processes and operational controls
  • Coordinate cross functional teams to ensure delivery and execution discipline

Qualifications
  • At least 7-10 plus years of experience in data integration, operations, and enterprise platforms
  • Strong experience managing incident processes, with an understanding of established banking frameworks and adherence to existing operating models
  • Ability to balance business demands while maintaining oversight of batch processing, ticketing, and SQL Server environments
  • Strong SQL and Python development skills
  • Expected to support and transition work to target platforms such as Python and Databricks
  • Ability to collaborate with the business on a daily basis and translate technical and functional needs
  • Demonstrated experience leveraging a wide variety of data analysis/Integration tools: SQL, Oracle/SQL Server, SSIS, Python, Pyspark, Databricks, Azure, ADF, Airflow, Tidal/Control-M, Snowflake
  • Balanced prioritization, and execution skills with Finance/Banking experience preferred.
  • Strong expertise in batch processing, data pipelines, and system integrations
  • Demonstrates strong knowledge and proficiency in data extraction, transformation, and analytics tools.
  • Strong operational governance, SLA management, and risk management skills
  • Clear communication and stakeholder engagement

Financial Services Experience Required:
  • Experience in fixed income, capital markets, and derivatives preferred
  • Strong understanding of financial products (including equities) to reduce onboarding time and accelerate business alignment

Nice to Have:
  • Experience with Databricks and Snowflake
  • Knowledge of semantic modeling and data modeling

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