Senior Data Analyst – Wealth Management

qode.world

Senior Data Analyst handling complex financial data analysis for wealth management clients in Austin, Texas. Collaborating with various teams to ensure data accuracy and integrity.

Posted 6/1/2026full-timeAustin • Texas • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

CloudETLNumpyPandasPySparkPythonSQL

About the role

Key responsibilities & impact

Explore and profile large, complex financial datasets to understand structure, lineage, gaps, and anomalies across custodian, portfolio, and transaction data.
Identify data relationships, patterns, and inconsistencies across source systems to inform data mapping, transformation logic, and business rules.
Conduct deep-dive analysis on wealth management data — including positions, returns, benchmarks, fees, and cash flows — to validate completeness and accuracy.
Document data dictionaries, field definitions, and business logic for use by both technical and non-technical teams.
Investigate data quality issues end-to-end, trace root causes across source systems, and recommend remediation approaches.
Engage directly with business stakeholders — advisors, portfolio managers, operations, and compliance — to gather, analyze, and document functional data requirements.
Translate business requirements into precise data logic, transformation rules, and acceptance criteria for downstream development and reporting.
Define and formalize calculation logic for KPIs such as AUM, performance returns, fee schedules, and client segmentation.
Review and validate business logic implemented in pipelines, data models, and reports to ensure alignment with requirements.
Act as a bridge between business teams and technology, ensuring data solutions are grounded in real operational needs.
Write complex SQL queries — including CTEs, window functions, and aggregations — to analyze datasets, build reusable logic, and support reporting and validation needs.
Validate pipeline outputs by querying source and target systems, reconciling counts, amounts, and key metrics to confirm data integrity.
Develop test cases and validation scripts to verify transformation logic, business rules, and data completeness after pipeline runs.
Use Python and/or Databricks notebooks for ad hoc data analysis, profiling, and validation where scale or complexity requires it.
Collaborate with engineering teams to review transformation logic, flag discrepancies, and verify that implemented pipelines match documented requirements.
Develop and maintain dashboards, reports, and KPI frameworks to support advisors, portfolio managers, and leadership.
Support client segmentation, performance reporting, AUM analysis, and investment strategy analysis.
Translate complex financial data findings into clear, concise narratives and recommendations for non-technical audiences.
Ensure all reporting outputs comply with financial regulations and internal data governance standards.

Requirements

What you’ll need

Bachelor's or Master's degree in Finance, Data Science, Business Analytics, or related field.
8-10+ years of experience in a data analyst role within wealth management, asset management, or institutional investments.
Expert-level SQL skills — complex multi-table joins, CTEs, window functions, subqueries, and analytical query design.
Strong ability to gather and analyze functional requirements from business stakeholders and translate them into data logic and acceptance criteria.
Proven experience with data discovery and profiling — understanding data structures, identifying quality issues, and documenting findings clearly.
Experience validating data pipelines or ETL outputs — reconciling source vs. target data, verifying business logic, and writing test cases.
Solid understanding of wealth management data — custodian feeds, portfolio holdings, performance returns, AUM, fees, and transactions.
Proficiency with Python for data analysis and ad hoc exploration (pandas, numpy); PySpark experience is a plus.
Familiarity with Databricks or similar cloud data platforms for querying and analyzing large datasets.
Understanding of data governance, data quality frameworks, and regulatory compliance in financial services.
Excellent communication and stakeholder management skills — comfortable presenting findings to both technical and business audiences.

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account qode.world Website LinkedIn All Job Openings 11 - 50 employees 🤖 Artificial Intelligence 👥 HR Tech 🎯 Recruiter Artificial Intelligence
HR Tech
Recruitment qode. world is a company that leverages artificial intelligence to revolutionize the recruiting process. Their platform allows users to find candidates by sourcing data from billions of data points worldwide and provides data-driven insights. Users can connect with candidates directly through the platform, conduct customized AI-led interviews, and get comprehensive assessments. The service also integrates easily with LinkedIn, enhancing the talent pool and facilitating direct communication with candidates listed there. Qode. world offers additional recruiting services to assist in hiring for niche or senior roles. They are praised for their effectiveness in streamlining the hiring process and delivering quick results. Senior Data Analyst – Wealth Management 🔥 3 minutes ago 🏢🏡 Austin – Hybrid ⏰ Full Time 🟠 Senior 📉 Data Analyst Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Explore and profile large, complex financial datasets to understand structure, lineage, gaps, and anomalies across custodian, portfolio, and transaction data.
Identify data relationships, patterns, and inconsistencies across source systems to inform data mapping, transformation logic, and business rules.
Conduct deep-dive analysis on wealth management data — including positions, returns, benchmarks, fees, and cash flows — to validate completeness and accuracy.
Document data dictionaries, field definitions, and business logic for use by both technical and non-technical teams.
Investigate data quality issues end-to-end, trace root causes across source systems, and recommend remediation approaches.
Engage directly with business stakeholders — advisors, portfolio managers, operations, and compliance — to gather, analyze, and document functional data requirements.
Translate business requirements into precise data logic, transformation rules, and acceptance criteria for downstream development and reporting.
Define and formalize calculation logic for KPIs such as AUM, performance returns, fee schedules, and client segmentation.
Review and validate business logic implemented in pipelines, data models, and reports to ensure alignment with requirements.
Act as a bridge between business teams and technology, ensuring data solutions are grounded in real operational needs.
Write complex SQL queries — including CTEs, window functions, and aggregations — to analyze datasets, build reusable logic, and support reporting and validation needs.
Validate pipeline outputs by querying source and target systems, reconciling counts, amounts, and key metrics to confirm data integrity.
Develop test cases and validation scripts to verify transformation logic, business rules, and data completeness after pipeline runs.
Use Python and/or Databricks notebooks for ad hoc data analysis, profiling, and validation where scale or complexity requires it.
Collaborate with engineering teams to review transformation logic, flag discrepancies, and verify that implemented pipelines match documented requirements.
Develop and maintain dashboards, reports, and KPI frameworks to support advisors, portfolio managers, and leadership.
Support client segmentation, performance reporting, AUM analysis, and investment strategy analysis.
Translate complex financial data findings into clear, concise narratives and recommendations for non-technical audiences.
Ensure all reporting outputs comply with financial regulations and internal data governance standards. 🎯 Requirements
Bachelor's or Master's degree in Finance, Data Science, Business Analytics, or related field.
8-10+ years of experience in a data analyst role within wealth management, asset management, or institutional investments.
Expert-level SQL skills — complex multi-table joins, CTEs, window functions, subqueries, and analytical query design.
Strong ability to gather and analyze functional requirements from business stakeholders and translate them into data logic and acceptance criteria.
Proven experience with data discovery and profiling — understanding data structures, identifying quality issues, and documenting findings clearly.
Experience validating data pipelines or ETL outputs — reconciling source vs. target data, verifying business logic, and writing test cases.
Solid understanding of wealth management data — custodian feeds, portfolio holdings, performance returns, AUM, fees, and transactions.
Proficiency with Python for data analysis and ad hoc exploration (pandas, numpy); PySpark experience is a plus.
Familiarity with Databricks or similar cloud data platforms for querying and analyzing large datasets.
Understanding of data governance, data quality frameworks, and regulatory compliance in financial services.
Excellent communication and stakeholder management skills — comfortable presenting findings to both technical and business audiences. Apply Now 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score Similar Jobs Senior Data Analyst 🕒 2 days ago SafeLease 11 - 50 🏠 Real Estate ☁️ SaaS Website LinkedIn All Job Openings Senior Data Analyst responsible for analyzing and interpreting data related to commercial real estate products at SafeLease. Collaborating closely with cross-functional teams for revenue growth and process automation. 🏢🏡 Austin – Hybrid ⏰ Full Time 🟠 Senior 📉 Data Analyst Energy Market Analytics Manager 🕒 May 2 Origis Energy 201 - 500 ⚡ Energy Website LinkedIn All Job Openings Energy Analytics Manager applying advanced modeling to assess market value at Origis Energy. Collaborating with Grid Analysis and Development teams in a full-time role. 🏢🏡 Austin – Hybrid ⏰ Full Time 🟠 Senior 🔴 Lead 📉 Data Analyst Data Analytics Analyst 🕒 March 17 Emerson 10,000+ employees 🏢 Enterprise ⚡ Energy ☁️ SaaS Website LinkedIn All Job Openings Principal Analytics Consultant delivering robust datasets and high‑quality dashboards for Emerson's sales and marketing teams. Collaborating closely with IT and Data Office on analytics capabilities modernization. 🏢🏡 Austin – Hybrid ⏰ Full Time 🟠 Senior 🔴 Lead 📉 Data Analyst 🦅 H1B Visa Sponsor Data Analyst, Data Intelligence 🕒 March 17 Acrisure 10,000+ employees 💸 Finance Website LinkedIn All Job Openings Data Analyst for Finance and Accounting functions in a fintech company. Leading reporting and analytics capabilities while collaborating with various stakeholders. 🏢🏡 Austin – Hybrid ⏰ Full Time 🟡 Mid-level 🟠 Senior 📉 Data Analyst 🦅 H1B Visa Sponsor Senior Merchant Analytics Manager 🕒 March 5 Upside 201 - 500 💸 Finance 🛒 Retail Website LinkedIn All Job Openings Senior Merchant Analytics Manager at Upside leveraging data to enhance merchant partnerships and drive product analytics. Leading analysis projects and collaborating with cross-functional teams. 🏢🏡 Austin – Hybrid 💵 $130k - $165k / year 💰 $100M Debt Financing on 2022-04 ⏰ Full Time 🟠 Senior 📉 Data Analyst 🦅 H1B Visa Sponsor View More Data Analyst Jobs 🌐 Worldwide Built by Lior Neu-ner. I'd love to hear your feedback — Get in touch via DM or support@remoterocketship.com Search Search Jobs by country Search jobs by city Search jobs by job title Search entry-level jobs Search junior-level jobs Search senior-level jobs Search jobs by tech stack Search jobs by contract type Search remote internships Search remote part-time jobs Remote jobs Anywhere in the World Companies Hiring Anywhere in the World Companies Hiring Sales People Anywhere in the World Companies Hiring Software Engineers Anywhere in the World Resources Advice Tips for finding remote jobs Interview questions and answers Resume examples Cover letter examples Post a job Affiliates Privacy policy Terms of service Job board SEO course AI Apply Copilot OpenClaw job finder Jobs by Country Remote jobs anywhere in the world (Worldwide remote jobs) Remote jobs United States Remote jobs Australia Remote jobs Brazil Remote jobs Canada Remote jobs France Remote jobs Ireland Remote jobs Germany Remote jobs Netherlands Remote jobs Spain Remote jobs UK Popular Jobs Remote data analyst jobs Remote customer support jobs Remote executive assistant jobs Remote marketing jobs Remote product designer jobs Remote product manager jobs Remote project manager jobs Remote recruiter jobs Remote sales jobs Remote software engineer jobs Jobs by Type Remote full-time jobs Remote part-time jobs Remote contract jobs Remote internship jobs Remote entry-level jobs Remote jobs with no experience required Remote junior jobs (1-3 years of experience) Digital nomad jobs Remote jobs with no degree required Freelance remote jobs Temporary remote jobs Remote jobs hiring now Stay at home mom jobs

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Hard Skills & Tools

SQLPythondata profilingdata validationETLdata mappingdata transformationKPI calculationdata analysisdata quality

Soft Skills

communicationstakeholder managementanalytical thinkingproblem-solvingdocumentationcollaborationpresentation skillsattention to detailrequirements gatheringnarrative translation