Data Analyst

TEKsystems•San Diego, CA

10d•$65 - $80•Hybrid

About The Position

The Senior Data Supply Chain Analyst is an expert-level individual contributor and subject matter expert who analyzes, documents, and improves financial and other data Cetera receives from external parties across the wealth management data supply chain. Reporting to the Head of Third-Party Data, the analyst works across hundreds of providers and feeds, tracing data from source files and intermediaries through ingestion, enterprise platforms, mastered data, reporting, and advisor and client experiences. The role translates complex data problems into evidence, confirmed root causes, and actionable recommendations to improve data quality and confidence in reporting, analytics, and business decisions. The role begins with the Product Sponsor Quality initiative and supports the broader third-party data remit, including product sponsors, custodians, clearing firms, transfer agents, recordkeepers, aggregators, market utilities, and technology and data providers. The analyst performs cross-source reconciliation and root-cause analysis and partners with internal teams and product sponsors to reduce data friction at its source. The work also supports Project Crystal Ball (PCB) and requires hands-on expertise with industry data feeds. This is a contract-to-hire position based in San Diego, California, with a hybrid workplace arrangement. The stated pay range is $65.00–$80.00 per hour. Subject to eligibility and applicable plan terms, benefits for this temporary role may include medical, dental and vision coverage; critical illness, accident and hospital coverage; a 401(k) retirement plan; voluntary life and AD&D insurance; short- and long-term disability; a health spending account; transportation benefits; an employee assistance program; and paid time off, vacation or sick leave.

Requirements

Bachelor's degree in a related field or equivalent.
At least 7 years of experience in data analysis, data quality, data operations, or data management, including significant hands-on experience with financial-services and wealth-management industry data feeds and enterprise-scale data quality initiatives.
Wealth management industry experience, including working knowledge of brokerage, advisory, custody, clearing, product sponsor, annuity and insurance, and retirement data flows.
Hands-on experience with industry data feeds, including sponsor and custodial feeds such as DST FAN Mail, BNY DAZL, DTCC/NSCC (including NSCC IPS and Payment aXis), and clearing-firm files from Pershing, NFS/Fidelity, and Schwab, aggregated through Broadridge/IDM (Investigo) and Albridge.
Recognized expertise in financial-services data flows and ability to independently diagnose complex cross-platform data issues spanning providers, intermediaries, enterprise systems, and business processes.
Strong SQL and advanced data-analysis skills, including profiling, reconciliation, comparison, and exception analysis across large data sets.
Ability to drive complex analyses and move issues, decisions, dependencies, and remediation to completion across teams.
Experience creating clear documentation, including data dictionaries, mappings, data-flow and lineage views, requirements, and operating procedures.
Ability to translate between business, operations, provider, architecture, engineering, governance, and data-quality perspectives.
Strong communication and presentation skills, including producing leadership-ready summaries and recommendations.
Ability to influence outcomes and drive resolution across multiple teams and external partners without direct management authority.
Demonstrated ability to apply AI, automation, or advanced analytics to improve efficiency and scale.

Nice To Haves

Securities Industry Essentials (SIE) exam; additional FINRA registrations are a plus. Active registration is not required unless role responsibilities require it.
Familiarity with data governance, metadata, lineage, master data management, reference data, and data catalog concepts.
Experience with Power BI or Tableau, Python or Power Query, APIs, and XML, JSON, or delimited-file handling.
Experience with industry data-feed coexistence, feed-suppression logic, and duplicate-transaction remediation in a broker-dealer environment.

Responsibilities

Establish and maintain source profiles, file specifications, data dictionaries, mappings, change histories, and known-issue logs for assigned providers and feeds.
Keep current the inventory of third-party providers, feeds, files, interfaces, business purposes, internal consumers, identifiers, and key contacts.
Maintain consistent reconciliation across Product Sponsors and contribute to a shared understanding of data completeness and quality.
Participate in designing the framework for Product Sponsor discussions and document source-to-consumer data flows, lineage, and attribute-level mappings to enterprise domains.
Establish and maintain documentation and analytical standards for third-party data analysis, reconciliation, and source assessments.
Serve as a subject matter expert for assigned providers, feeds, and data domains, advising internal teams and business stakeholders on sourcing, mappings, lineage, and issue resolution.
Analyze industry and proprietary data feeds and trace their movement through clearing-firm files, aggregators, and downstream systems.
Perform cross-source profiling, reconciliation, and gap analysis of accounts, positions, transactions, balances, identifiers, and mappings; quantify scale and business impact.
Investigate complex data issues, distinguish symptoms and failure points from confirmed root causes, and execute appropriate analysis.
Translate technical findings into business impact, executive-ready summaries, visualizations, and recommendations for prioritization, investment, and remediation.
Prepare evidence-based issue packages and participate in working sessions with external providers, aggregators, and internal relationship owners; track decisions, dependencies, and remediation through resolution.
Build and maintain provider and feed scorecards covering completeness, timeliness, rejects and exceptions, recurrence, reconciliation, and remediation progress.
Support provider-facing data expectations and change-management standards with relevant internal teams.
Identify systemic patterns across feeds and recommend scalable preventive solutions.
Develop and promote reusable templates, playbooks, standards, analytical frameworks, and automation capabilities; share approaches and lessons learned with peers.
Perform other duties as assigned.