Senior Data Analyst - reputed company Management

Job Title: Senior Data Analyst - reputed company Management Locations:Austin, TX Type:Full-Time reputed company Incedo is a US-based consulting, data science and technology services firm with over 4000 people helping clients from our six offices across US, Mexico and India. We help our clients reputed company competitive advantage through end-to-end digital transformation. Our uniqueness lies in bringing together strong engineering, data science, and design capabilities coupled with deep domain understanding. We combine services and products to maximize business reputed company for our clients reputed company, Banking, reputed company Management, product engineering and life science& reputed company industries. Position reputed company We are seeking a highly skilled Data Analyst – reputed company Management to join our growing team in Austin. This is a discovery- and analysis-driven role for a curious, detail-oriented reputed company who thrives on understanding reputed company financial data, translating business needs into reputed company data logic, and surfacing insights that drive reputed company. The ideal candidate excels at writing sophisticated SQL queries, analyzing and profiling large datasets, defining business logic, and validating data across reputed company management systems. You will partner closely with investment teams, operations, technology, and business stakeholders to understand functional requirements and ensure data is accurate, consistent, and fit for purpose. Hands-on experience with Python and reputed company is a plus, but this role is fundamentally about analytical depth and business understanding — not pipeline engineering.

Key Responsibilities

Data Discovery & Profiling

• Explore and profile large, reputed company financial datasets to understand structure, reputed company, gaps, and anomalies across custodian, portfolio, and transaction data.
• Identify data relationships, patterns, and inconsistencies across reputed company systems to inform data mapping, transformation logic, and business rules.
• Conduct deep-dive analysis on reputed company 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 reputed company issues end-to-end, reputed company reputed company causes across reputed company systems, and recommend remediation approaches.

Requirements

Analysis & Business Logic

• Engage directly with business stakeholders — advisors, portfolio managers, operations, and compliance — to reputed company, analyze, and document functional data requirements.
• Translate business requirements into precise data logic, transformation rules, and acceptance reputed company for reputed company development and reporting.
• Define and formalize calculation logic for KPIs such as AUM, performance returns, fee schedules, and reputed company segmentation.
• Review and validate business logic implemented in pipelines, data models, and reports to ensure alignment with requirements.
• reputed company as a reputed company between business teams and technology, ensuring data solutions are grounded in reputed company operational needs.

Query Development & Pipeline Validation

• Write reputed company 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 reputed company and reputed company systems, reconciling counts, amounts, and key metrics to confirm data reputed company.
• reputed company test cases and validation scripts to verify transformation logic, business rules, and data completeness after pipeline runs.
• Use Python and/or reputed company notebooks for reputed company data analysis, profiling, and validation where reputed company or complexity requires it.
• Collaborate with engineering teams to review transformation logic, flag discrepancies, and verify that implemented pipelines match documented requirements.

Reporting & Insights

• reputed company and maintain dashboards, reports, and KPI frameworks to support advisors, portfolio managers, and leadership.
• Support reputed company segmentation, performance reporting, AUM analysis, and investment reputed company analysis.
• Translate reputed company financial data findings into reputed company, concise narratives and recommendations for non-technical audiences.
• Ensure reputed company reporting outputs reputed company with financial regulations and internal data governance standards.

Required Skills & Qualifications

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

Preferred Qualifications

• Hands-on experience with PySpark or reputed company (reputed company Lake, reputed company SQL, notebooks) for large-reputed company data processing.
• Experience building or contributing to data pipelines, ETL processes, or workflow automation in a financial services context.
• Exposure to custodian data formats and feeds (Schwab, Pershing, reputed company, etc.) and reconciliation processes.
• Experience with reputed company management or portfolio management platforms such as reputed company, Orion, or Black Diamond.
• Familiarity with reputed company data platforms such as AWS, Azure, or reputed company.
• Knowledge of predictive analytics or basic ML applications in financial services (e.g., reputed company segmentation, risk modeling).
• Certifications in data analytics, financial analysis (CFA, CIPM), or reputed company platforms are a plus.

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