Senior Level Data Operations Manager Jobs
Senior level data operations manager jobs put experienced professionals in charge of data pipeline strategy, operational governance, and the cross-functional teams that keep enterprise data systems running at scale. Hiring is concentrated in Electronics & Hardware, Technology & Software, and Construction & Real Estate, with a mix of on-site, remote, and hybrid positions available, and employers like Apple, Digital Realty, and Amazon hiring at this level now.
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We provide a foundation of stability and predictability that gives employees the confidence to succeed.
Founded in 1967, W. R. Berkley Corporation has grown from a small investment management firm into one of the largest commercial lines property and casualty insurers in the United States.
Along the way, we’ve been listed on the New York Stock Exchange, become a Fortune 500 Company, joined the S&P 500, and seen our gross written premiums exceed $15 billion.
Today the Berkley brand comprises 60 businesses worldwide and is divided into two segments: Insurance and Reinsurance and Monoline Excess. Led by Chairman, President and Chief Executive Officer, W. Robert Berkley, Jr., W. R. Berkley Corporation is well positioned for long-term success and future growth.
The Company is an equal employment opportunity employer.
Responsibilities:
The role provides technical and functional support for Oracle Essbase, Oracle Analytics Server, PeopleSoft financial data, Vena, BDW, ledger-related processes, data warehouse integrations, and financial reporting data flows.
The position is responsible for supporting recurring production processes, troubleshooting data and reporting issues, maintaining and enhancing Essbase cubes and related jobs, assisting with ledger and financial close data validation, and partnering with business and technology teams to improve the reliability, scalability, and transparency of finance data.
This position requires the ability to translate finance and accounting requirements into technical solutions; develop and maintain reports, databases, scripts, queries, integrations, and ETL/ELT processes; support production operations; assist with system upgrades and platform transitions; and communicate effectively with internal business users, technology partners, vendors, and operating unit stakeholders.
Key Functions/Duties of Position:
- Design, develop, maintain, and support finance data architecture, data warehouse structures, ETL/ELT processes, scripts, queries, reports, dashboards, cubes, and analytical environments used by Corporate Finance and operating units.
- Participate in Databricks modernization efforts by helping identify legacy finance data processes to migrate, refactor existing data jobs, validate results between legacy and Databricks environments, support workflow orchestration, and help establish scalable data processing patterns.
- Assist with the transition from legacy SQL Server, DataStage, SSIS, OAS, Essbase, and other existing data processes toward Databricks and modern lake house-based architecture where appropriate.
- Support AI and automation initiatives by helping prepare trusted finance data, define business rules, identify exception-handling opportunities, improve metadata and semantic definitions, and enable self-service analytics, AI-assisted inquiry, and governed data access.
- Provide ongoing production support for Oracle Essbase, Oracle Analytics Server, PeopleSoft warehouse data, Vena integrations, BDW reporting processes, and related financial reporting platforms.
- Monitor recurring finance data processes, including nightly and monthly cube refreshes, data loads, job failures, close-related processing, and system-generated exception messages; investigate issues and coordinate timely resolution.
- Maintain, troubleshoot, and enhance Essbase cubes and related reporting structures, including PeopleSoft company cubes, BDW cubes, Schedule P, Schedule F, corporate dashboard, auditing, allocation, and other financial reporting use cases.
- Support ledger and financial close processes by assisting with hierarchy maintenance, new general ledger accounts, close error monitoring, PeopleSoft data validation, month-end close reporting, balancing, reconciliation, and downstream reporting impacts.
- Partner with Corporate Finance, operating units, actuarial teams, and other technology teams to define requirements, resolve data issues, validate results, and implement reporting and data integration improvements.
- Develop and maintain documentation for processes, data flows, system dependencies, controls, validations, support procedures, and modernization changes to reduce key-person risk and improve long-term supportability.
- Provide technical analysis and support for finance data requests, including historical general ledger data, BDW validation, premium, loss, producer, expense, reinsurance, allocation, and other financial or operational datasets.
- Assist with ServiceNow requests, security access, user support, Smart View and reporting access, data availability questions, and troubleshooting for finance reporting users.
- Participate in system maintenance, upgrades, disaster recovery planning, server migrations, platform testing, and production deployment activities for finance data and reporting systems.
- Apply sound development and support practices, including code review, testing, documentation, version control, issue tracking, deployment coordination, and clear communication of risks, dependencies, and downstream impacts.
- Provide strategic and technical leadership for the Financial Data and Analysis team and business partners, establishing priorities and accountability across recurring production support, financial data architecture, reporting platforms, data quality, and modernization initiatives while ensuring reliable, scalable, and well-controlled delivery of finance data solutions.
- Lead, coach, and develop team members by providing clear technical direction, strengthening knowledge of finance data structures and reporting environments, and promoting disciplined practices for testing, documentation, controls, issue resolution, and change management, while building the team’s capabilities in Databricks, AI-enabled analytics, automation, and modern lake house technologies.
Qualifications:
- Bachelor’s degree or equivalent; preferably in actuarial science, math or computer science.
Qualifications:
- 12-15+ years of experience in finance data architecture, data engineering, business intelligence, financial reporting systems, data warehousing, analytics, or related technical support roles.
- Strong SQL experience, preferably with Microsoft SQL Server and enterprise financial data warehouse environments.
- Experience leading or managing a team.
- Experience developing, maintaining, or supporting ETL/ELT processes, data integrations, data pipelines, batch jobs, and production data workflows.
- Experience with Databricks, lake house architecture, Unity Catalog, Databricks SQL, notebooks, workflow orchestration, APIs, or cloud-based data modernization preferred.
- Familiarity with AI-enabled analytics, semantic layers, metadata management, business definitions, exception detection, automation, and self-service finance reporting preferred.
- Experience with Oracle Essbase, Oracle Analytics Server, Smart View, financial reporting cubes, dimensional structures, metadata, and cube refresh or maintenance processes.
- Experience supporting finance, accounting, ledger, close, planning, budgeting, reconciliation, allocation, or statutory reporting processes.
- Strong project management, organizational, prioritization, and planning skills, including the ability to manage competing demands, recurring production responsibilities, and modernization initiatives.
- Working knowledge of financial data, general ledger structures, chart fields, accounting hierarchies, month-end close processes, and downstream reporting dependencies preferred.
- Ability to understand complex finance, accounting, actuarial, and insurance reporting requirements and translate them into effective data and technology solutions.
- Strong analytical, critical thinking, troubleshooting, and problem-solving skills, with the ability to diagnose root causes across data, process, system, and business-rule issues.
- Demonstrated ability to work effectively across Corporate Finance, operating units, actuarial, technology, data governance, vendor, and support teams.
- Strong communication skills, including the ability to explain technical issues to business users, document support procedures, and summarize risks, dependencies, and recommended actions.
- Demonstrated commitment to data quality, control, auditability, documentation, supportability, and customer service.
- Multi-line property and casualty insurance experience is beneficial.
- Ability to work independently, exercise sound judgment, and provide leadership in ambiguous or evolving technical and business environments.
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Top Industries Hiring
- Electronics & Hardware
- Technology & Software
- Construction & Real Estate
- Telecommunications
- Insurance
Senior Level Data Operations Manager Jobs: Frequently Asked Questions
How do I get a senior level data operations manager job?
Employers hiring at this level look for candidates who have owned end-to-end data operations, not just contributed to them. Demonstrated experience leading teams, designing scalable data workflows, and driving decisions through data quality and governance gives candidates the clearest edge. Strong familiarity with cloud platforms, data orchestration tools, and stakeholder communication across business and technical teams distinguishes senior applicants from mid-level ones.
Which companies hire senior level data operations managers?
Companies hiring senior level data operations managers right now include Apple, Digital Realty, and Amazon, based on current listings on Migrate Mate as of November 2026. Hiring at this level tends to concentrate among large enterprises, technology-driven organizations, and data-intensive businesses that rely on mature data infrastructure to support their operations and decision-making.
Are there remote senior level data operations manager jobs?
Yes, remote and hybrid opportunities are widely available at this level. About 18% of senior level data operations manager openings are remote or hybrid as of November 2026, reflecting strong demand from organizations comfortable with distributed leadership for data functions. On-site roles remain common at companies with complex, regulated, or on-premise data environments.
What makes a data operations manager role senior level?
Senior level roles are defined by scope, ownership, and leadership responsibility. Where mid-level roles execute within established systems, senior roles set direction, own outcomes across data pipelines or platforms, and are accountable for the technical quality of the broader data operation. Mentoring junior team members, managing cross-functional stakeholder relationships, and influencing data strategy are consistent expectations at this stage.
Which industries hire the most senior level data operations managers?
Senior level data operations manager roles concentrate in Electronics & Hardware, Technology & Software, and Construction & Real Estate, based on current listings on Migrate Mate as of November 2026. These sectors drive demand because they operate at high data volume and complexity, requiring experienced leaders who can build reliable, scalable data systems rather than simply maintain existing ones.