Asset Management Data SME / Data Validation

• Drive Silver and Gold layer data reconciliation and sign-off activities.
• Rapidly evaluate and disposition reconciliation differences.
• Identify and document root causes and remediation actions.
• Escalate material risks that could impact Aladdin readiness.
• Improve transparency of lineage, calculations, and data quality controls.
• Enable timely and confident business sign-off of data products and reporting outputs.

• Strong understanding of positions/holdings, security reference data, pricing/market data, performance/benchmarks, risk/analytics and portfolio data
• Experience in large-scale data reconciliation, root-cause analysis, data lineage, and Silver/Gold layer validation and sign-off
• Ability to work across business and technology teams to investigate and resolve data exceptions
• Aladdin implementation/migration/onboarding experience is highly preferred, * Strong SQL and Snowflake experience with the ability to extract, analyze, and reconcile data across large and complex datasets.

• Deep understanding of asset management data domains, including:

• Positions & Holdings
• Security Reference Data
• Pricing & Market Data
• Performance & Benchmark Data
• Analytics & Risk Data
• Product and Portfolio Structures
• Experience validating and signing off data products used for downstream reporting, analytics, operational processes, and business consumption.
• Ability to analyze data outputs and trace lineage end-to-end across source systems, Snowflake, medallion architecture layers (Bronze, Silver, Gold), and consuming applications.

• Strong investigative skills to determine whether variances are driven by:

• Data sourcing issues
• Mapping or transformation logic
• Calculation methodologies
• Reference data differences
• Expected business or vendor differences
• Experience performing large-scale data reconciliations and validating data conversions, migrations, and platform implementations.
• Ability to quickly research, troubleshoot, and perform root cause analysis on complex data exceptions and reconciliation breaks.
• Proficient in using AI-assisted analysis tools to accelerate data investigations, anomaly identification, reconciliation review, and documentation activities.
• Ability to understand and evaluate data calculations, transformation logic, business rules, and reporting outputs.
• Experience documenting data lineage, business glossaries, transformation logic, and data definitions as part of the validation process.
• Ability to identify recurring issue themes and proactively recommend data quality controls, monitoring requirements, and DQ rules.
• Strong communication skills with the ability to summarize findings, risks, root causes, and recommended actions for both technical and business stakeholders.
• Ability to independently manage workstreams, drive issue resolution, and lead sign-off activities with minimal oversight.

Preferred Qualifications

• Prior Aladdin implementation, migration, onboarding, or support experience.
• Understanding of Aladdin data models, security master, analytics, positions, pricing, and downstream reporting integrations.
• Experience working within modern data platforms leveraging Snowflake and medallion architecture patterns.
• Familiarity with data lineage, metadata, governance, and data quality tooling.
• Previous experience supporting enterprise data platform transformations, operating model changes, or data validation programs within an asset management environment.

• $85,000-105,000 per year Over the last 20 years, Ares’ success has been driven by our people and our culture. Today, our team is guided by our core values - Collaborative, Responsible, Entrepreneurial, Sel…

• 1 month ago + *