Data Integration Operations Manager

Madison-Davis, LLC; New York (NY); On-site; USD 140,000 - 190,000; Full time

Job summary

Madison-Davis, LLC seeks a Senior Data Integration Operations Manager in New York to orchestrate critical data flows across business, operations, and technology teams.

The role blends production operations, data integration, incident management, and platform modernization as legacy tools shift to cloud‑forward architectures. You will coordinate with offshore partners and SMEs during time‑sensitive events, ensuring SLA adherence and robust data pipelines.

Qualifications

• 7–10+ years in data integration, production ops, or enterprise data platforms.
• Strong hands‑on SQL and Python skills.
• Experience supporting production pipelines, batch processing, and SLA workflows.
• Financial services or banking domain with capital markets exposure.
• Ability to communicate operational impact across tech and business teams.
• Experience with incident management, governance, and release discipline.
• Familiar with SQL Server, SSIS, Oracle or comparable legacy tools.
• Exposure to Databricks, PySpark, Spark, Azure, ADF, Airflow, Control‑M, Tidal, Snowflake.
• Understanding AI-assisted tools to boost productivity without replacing judgment.
• Collaborative, low‑ego style with ownership and follow‑through.

Responsibilities

• Own daily visibility across integration ops, batch workflows, and production pipelines.
• Coordinate with offshore teams to identify incidents, SLA risks, and blockers.
• Partner with SMEs to improve resiliency, monitoring, docs, controls, and execution.
• Stabilize SQL Server and SSIS workflows while contributing to cloud modernization.
• Support incident response, root‑cause analysis, risk management, and SDLC.
• Work across capital markets data areas: market, reference, fixed income, equities, derivatives.
• Advance modern data platforms using Spark, PySpark, Databricks, governance, Medallion patterns.

Skills

SQL

Python

Batch processing

Data integration

Incident management

Cloud data platforms

Databricks

Spark

Azure

Airflow

Tools

SQL Server

SSIS

Oracle

Databricks

Airflow

Control-M

Tidal

Snowflake

Job description

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

What You Bring:

• 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

Nice to Have:

• 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