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Data Integration Operations Manager
Job in
New York, New York County, New York, 10261, USA
Listed on 2026-08-28
Listing for:
Madison-Davis, LLC
Full Time
position Listed on 2026-08-28
Job specializations:
-
IT/Tech
Data Engineering
Job Description & How to Apply Below
A global financial institution is seeking a senior Data Integration Operations Manager to support critical enterprise data flows across business, operations, and technology stakeholders. This role sits at the intersection of production operations, data integration, incident management, and platform modernization.
The team is managing an active transition from legacy integration tools toward a more cloud-forward, AI-enabled data architecture. The right person will be hands‑on enough to understand SQL, Python, batch workflows, and pipeline behavior, while also able to coordinate across SMEs, offshore partners, and business‑facing teams during time‑sensitive production events.
What You’ll Tackle:- Own daily visibility across integration operations, batch workflows, and production data pipelines
- Coordinate with offshore teams at the start of the day to identify incidents, SLA risks, and operational blockers
- Partner with senior SMEs to improve resiliency, monitoring, documentation, controls, and execution discipline
- Help stabilize existing SQL Server and SSIS-based workflows while contributing to cloud data modernization
- Support incident response, root‑cause analysis, operational risk management, and SDLC expectations
- Work across capital markets data areas such as market data, reference data, fixed income, equities, and derivatives
- Contribute to the evolution of modern data platforms using Spark, PySpark, Databricks, governance, and Medallion‑style architecture patterns
- 7 to 10 plus years of experience in data integration, production operations, enterprise data platforms, or related technology environments
- Strong hands‑on SQL and Python skills
- Experience supporting production data pipelines, batch processing, integrations, and SLA‑driven workflows
- Financial services or banking domain experience, preferably with exposure to capital markets
- Ability to understand and communicate operational impact across technical and business teams
- Experience with incident management, operational governance, release discipline, and production support
- Familiarity with SQL Server, SSIS, Oracle, or comparable legacy data integration environments
- Exposure to modern data platforms such as Databricks, PySpark, Spark, Azure, ADF, Airflow, Control‑M, Tidal, or Snowflake
- Practical understanding of how AI‑assisted tools can improve productivity without replacing core technical judgment
- Collaborative, low‑ego communication style with strong ownership and follow‑through
- Databricks or PySpark implementation experience
- Medallion architecture or lakehouse data platform exposure
- Experience modernizing on‑prem data platforms into cloud‑native ecosystems
- Knowledge of market data, reference data, fixed income, equities, derivatives, repo, collateral, risk, or regulatory reporting
- Experience working with distributed or offshore support teams
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