Client Financials Solutions Lead – Director

Role Overview

• Define and execute the multi-year technology roadmap and strategy for the Client Financials portfolio, ensuring alignment with enterprise architecture standards, data governance, and business priorities.
• Provide ownership and tech direction for all Client Financials products, driving innovation and continuous improvement across the platform.
• Implement key Revenue and Expense attribution methodologies to standardize reporting of accurate client returns.
• Build and sustain trusted, strategic relationships with senior business counterparts, finance leadership, and enterprise technology partners.
• Drive the execution of high-priority, cross-functional programs in partnership with business, infrastructure, security, data and architecture teams — ensuring delivery commitments are met with quality and predictability.
• Hold peer leaders in testing, architecture, infrastructure, and other partner functions accountable for their contributions to shared delivery outcomes.
• Own and oversee the technology book of work for the Client Financials portfolio, including planning, forecasting, and financial governance to ensure targets are met and investments are optimized.
• Establish and maintain robust project tracking, reporting, and governance frameworks to provide transparency on delivery progress, risks, and resource utilization.
• Lead and manage engineering teams to deliver business and technology value with a relentless focus on velocity, quality, and agility.
• Champion and institutionalize modern engineering practices including Scaled Agile (SAFe), DevOps, CI/CD, infrastructure-as-code, and end-to-end automation.
• Evangelize / introduce new technologies (including AI) to business partners that offer high-performance with low technology footprint.

Requirements

• In-depth expertise with Ab Initio for enterprise-grade, high-volume ETL pipeline development and orchestration.
• Deep expertise in Apache Superset, Apache Druid, Apache Pinot and other OLAP, multidimensional Cube technologies, and analytical query optimization for complex financial reporting.
• Experience in constructing highly performant, scalable, bitemporal data models for data marts, attribution engines, and analytical processing layers.
• Proficiency in Python-based data engineering, automation, pipeline orchestration, and tooling development.
• Proficiency in Apache Spark and PySpark for large-scale distributed data transformation, enrichment, and aggregation pipelines.
• Strong background in designing resilient, idempotent data integration patterns across heterogeneous source systems.
• Extensive hands-on experience with the Hadoop ecosystem (HDFS, YARN, MapReduce) for large-scale data processing.
• Expertise in Parquet and Iceberg formats.
• Expertise in Hive, Impala for high-throughput SQL-on-Hadoop analytical workloads.
• Knowledge of Google BigQuery for cloud-native analytical processing and ad-hoc financial analysis at scale.
• Functional knowledge of Institutional businesses and banking rules related to capital and liquidity metrics, such as Risk Weighted Assets (RWA), Stress Capital Buffer, Resolution Liquidity Adequacy and Positioning, etc.
• Demonstrated ability to influence remote, senior stakeholders, including senior business executives.
• Experience in tracking and monitoring delivery, productivity, and organizational health metrics.
• Experience planning, forecasting, and managing a technology book of work at the team level, including project tracking and governance.
• Demonstrated systems thinking, critical analysis, and design thinking skills.
• Ability to work in a globally matrixed environment and partner with virtual teams and external partners.

Tech Stack

• Apache
• BigQuery
• Cloud
• ETL
• Hadoop
• HDFS
• MapReduce
• PySpark
• Python
• Spark
• SQL
• Yarn

Benefits

• medical, dental & vision coverage
• 401(k)
• life, accident, and disability insurance
• wellness programs
• paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays