Technical Data Analyst

Job Description

Job Description

Technical Data Analyst

Location: Jersey City

Hybrid: Yes, 3 days onsite

Interview: 3 to 4 rounds (w/ and onsite interview)
Contract: Yes 6+ Months
Converion: Yes

We are seeking an experienced Technical Data Analyst with strong expertise in Master Data Management (MDM), financial data domains, and enterprise data platforms within the Financial Services industry. This role will function as a key member of the Data organization supporting enterprise data initiatives focused on Security Master, Account, Benchmark, Client, and other critical master and reference data domains.

The ideal candidate will combine strong analytical and data domain expertise with hands-on experience supporting MDM implementations, data integration, data mapping, and enterprise data warehouse initiatives. The role requires deep familiarity with financial market data, fund accounting platforms, wealth management data environments, and modern cloud-based data platforms.

This position will serve as a Subject Matter Expert (SME) for master and reference data management, data sourcing, data quality, and integration of legacy financial data platforms into modern enterprise data ecosystems.

Key Responsibilities:
• Act as a Subject Matter Expert (SME) for Master Data Management (MDM) initiatives across Security Master, Account, Client, Benchmark, and related financial data domains.
• Analyze, profile, and document enterprise data flows, business rules, and data lineage across financial systems and data platforms.
• Contribute to the development and execution of the organization's data strategy, aligning data initiatives with business goals.
• Support enterprise MDM implementation and modernization initiatives involving legacy and cloud-native data platforms.
• Support the implementation of scalable data architecture and frameworks to enable advanced analytics and reporting.
• Perform detailed data analysis, data mapping, source-to-target mapping, and reconciliation activities across multiple financial data sources.
• Collaborate with data architects, data engineers, governance teams, and business stakeholders to define and manage enterprise master and reference data standards.
• Support integration of MDM platforms and legacy financial systems into enterprise data lake, warehouse, and cloud data ecosystems.
• Develop strong familiarity with enterprise financial datasets and serve as a trusted data SME for downstream analytics, operational, and reporting teams.
• Work with market data providers, internal operational systems, accounting platforms, and external reference data feeds to ensure data consistency and accuracy.
• Support data quality initiatives including validation, issue analysis, exception management, and governance processes.
• Partner with engineering and platform teams supporting cloud-based data platforms and modern data architecture initiatives.
• Assist in defining data governance standards, metadata management, lineage tracking, and operational data controls.
• Support enterprise reporting, analytics, risk, compliance, and operational data initiatives.

Required Skills & Experience:
• 5–6 years of experience in data analysis, data engineering, or a related technical role.
• Strong experience in Master Data Management (MDM) and enterprise data analysis.
• Drive initiatives around data standardization, metadata management, and data cataloging.
• Expertise with financial master and reference data domains including Security Master, Account, Benchmark, Client, and related financial datasets.
• Experience with MDM platforms such as GoldenSource or similar enterprise MDM solutions.
• Strong understanding of financial services data ecosystems and operational data flows.
• Experience with fund accounting, wealth management, custody, investment operations, or related financial platforms.
• Understanding data modeling, data warehousing, and data integration concepts.
• Familiarity with market data providers, reference data feeds, and financial instrument data structures.
• Experience performing data mapping, source-to-target analysis, reconciliation, and data lineage documentation.
• Strong SQL and data analysis skills with the ability to analyze large and complex datasets.
• Understanding of enterprise data warehouse, data lake, and modern cloud data platform architectures.
• Familiarity with cloud-based data platforms and technologies including Databricks, Spark, and distributed data environments.
• Experience collaborating with data engineering, architecture, governance, and analytics teams.
• Knowledge of metadata management, data quality, and governance processes.
• Experience supporting data integration initiatives across legacy and modern enterprise platforms.
• Understanding of financial industry regulatory, operational, and reporting data requirements within U.S. financial institutions.

Preferred Qualifications:
• Financial Services, Asset Management, Wealth Management, or Banking industry experience strongly preferred.
• Exposure to enterprise data modernization and cloud migration initiatives.
• Familiarity with Azure, AWS, or other cloud-native data ecosystems.
• Experience supporting analytics, reporting, and enterprise data consumption platforms.
• Strong communication, documentation, and stakeholder management skills.
• Ability to function as a trusted SME within enterprise data programs and cross-functional initiatives.

Education:
Bachelor's degree in Computer Science, Information Systems, Finance, Engineering, Mathematics, or related field.