Senior Director - Client Data Solutions
Remote · United States or Wauwatosa, Wisconsin, United States
Job Summary
Lead data engineering, integration engineering, and client reporting teams to define and deliver end-to-end client data ecosystem, including integrations with ATS and external systems; own the design and delivery of scalable, templated analytics-ready data products and dashboards; establish KPIs, data quality, and governance; partner with Product Management, AI Engineering, and Client Services to align data capabilities with product strategy and long-term platform evolution; drive data architecture, integration patterns, and platform scalability while ensuring security, regulatory compliance, and production readiness.
Required Qualifications
- Bachelor's degree strongly preferred
- 8+ years of experience in data engineering, data platforms, or integration roles
- 5+ years leading technical teams, including managing managers
- Deep experience with modern data architecture, ETL/ELT, and integration frameworks
- Proven track record of delivering client-facing data solutions or data products at scale
- Experience with AWS and Azure, Apache Airflow, Docker, Python (Pandas), Snowflake, PostgreSQL, NoSQL
- Experience with API design, development, and integration patterns
- Experience with AI/ML teams to support data requirements
- Knowledge of data governance, security, and compliance requirements
- Proficiency in data quality management and monitoring tools
Desired Qualifications
- Bachelor's degree strongly preferred
- 8+ years of experience in data engineering, data platforms, or integration roles
- 5+ years of experience leading technical teams, including managing managers
- Deep experience with modern data architecture, ETL/ELT, and integration frameworks
- Proven track record of delivering client-facing data solutions or data products at scale
- Strong understanding of AWS, Microsoft Azure, Apache Airflow, Docker, Python (Pandas), RDBMS (Snowflake, PostgreSQL), and NoSQL (Redis, DynamoDB)
- Experience with API design, development, and integration patterns
- Experience working with AI/ML teams to support data requirements for model development and deployment
- Knowledge of data governance, security, and compliance requirements
- Proficiency in data quality management and monitoring tools
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