Vice President, Data Quality Platform

About this role About this role Our Data Quality Platform is a critical component of the Aladdin Data ecosystem, ensuring that data powering investment analytics and business workflows is accurate, consistent, and trustworthy at scale. The platform provides a unified framework for data profiling, validation, reconciliation, observability, and governance across high-volume financial datasets. What You will do As a Vice President, Aladdin Data Quality Platform, you will play a key role in building and evolving this platform—developing scalable services and frameworks that proactively measure, enforce, and monitor data quality across the enterprise. You will help create a seamless and extensible system that integrates with upstream and downstream data platforms, enabling continuous data reliability. Key Responsibilities Build and scale data quality services and APIs that provide rule execution, scoring, and quality SLAs for datasets and domains Define and implement data quality frameworks : rules engine patterns, validation layers, quality gates, and exception workflows Establish data profiling and anomaly detection capabilities (completeness, distribution drift, outliers, schema drift) Implement reconciliation controls (source-to-target, balancing, row counts, sums/hashes, financial totals checks) Design metadata-driven quality rules : configurable rules, versioning, ownership, and auditable execution history Engineer quality controls across ingestion/processing: schema enforcement, type checks, nullability constraints referential integrity checks Support data lineage and traceability and data observability : Optimize high-volume query workloads in Snowflake/MSSQL while maintaining consistent quality checks at scale Partner with platform, governance, and product teams to drive long-term strategy for trusted data quality services Mentor engineers and influence architectural direction for enterprise-grade data quality platforms Required Qualifications 10 years of backend/data platform engineering with strong hands-on development Deep expertise in Python and modern API frameworks such as FastAPI Strong experience building scalable services for data platforms (APIs, pipelines, controls) Strong hands-on experience with Snowflake and/or MSSQL , including performance tuning Proven experience implementing data quality controls across batch and/or streaming pipelines Experience with data quality operating models : quality SLAs/SLOs (freshness, accuracy, completeness) issue triage workflows, exception handling, and remediation Strong knowledge of data modelling (relational, dimensional, analytical) and model validation techniques Experience designing reconciliation frameworks and audit-grade controls (esp. for financial data) Familiarity with distributed systems, containerization (Docker), and CI/CD pipelines Bachelor’s/Master’s in CS/Engineering or equivalent experience Preferred Qualifications Experience with data quality tools/frameworks (any of): Great Expectations, Soda, dbt tests, Bigeye(or equivalent in-house frameworks) Exposure to event-driven architectures (Kafka or similar) for near-real-time quality detection Experience with Kubernetes and cloud-native platforms (AWS/Azure/GCP) Understanding of Domain-Driven Design (DDD), especially around data domains and ownership boundaries Technical Skills Python, FastAPI Snowflake, MSSQL Data Quality Framework Design (rules, scoring, gates) Data Profiling, Validation, Reconciliation Metadata-driven systems (rule catalogs, versioning, audit) Data Observability (freshness, volume, schema drift, SLAs) Data Lineage & Governance integrations Data Pipelines (ETL/ELT; batch/streaming) High-Volume Query Optimization Docker / Kubernetes, CI/CD Our benefits To help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents ... (truncated, view full listing at source)