Lead Data Engineer, Master Data Management
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Job Description
Lead data engineer building pipelines, governance, and master data systems for Clearstead, a financial advisory firm. Driving Databricks quality, integration, and enterprise data standards.
Responsibilities:
- Design and implement real-time and batch data processing solutions for modeling, analytics, and reporting
- Develop and maintain scalable data pipelines and API integrations
- Build and manage complex datasets
- Develop database applications and data integration layers using database programming languages, ETL tools, and scripting languages
- Establish and promote data engineering standards, documentation, coding practices, and technical best practices
- Apply security standards and controls to protect enterprise data and code
- Connect data across cloud, multicloud, and on-premises environments
- Research and recommend enhancements to database design, development practices, tools, and platform capabilities
- Partner with data scientists and business teams on modeling, reporting, data processing, and visualization needs
- Troubleshoot data design, engineering, and integration issues
- Develop and implement enterprise data governance policies, standards, and ownership frameworks
- Establish unified records for clients, households, legal entities, and accounts
- Lead data matching, entity resolution, duplicate identification, and stewardship processes
- Establish business definitions, data dictionaries, and certification standards
- Design and implement automated data quality checks, reconciliation processes, and remediation procedures
- Co-own the Databricks platform, including Unity Catalog and data access controls
- Provide second-line support for the Databricks platform
- Monitor data integrity and resolve quality issues across enterprise systems
- Support data integration and standardization following acquisitions
- Establish and lead cross-functional data ownership and governance forums
- Standardize data definitions and resolve inconsistencies with business leaders
- Communicate data quality findings, risks, and improvement opportunities
- Drive accountability for enterprise data quality and governance standards
- Chair the firm’s quarterly review of AI agents
- Collaborate across wealth management, investments, operations, finance, compliance, and technology
Requirements:
- Bachelor’s degree in Data Management, Information Systems, Computer Science, Business Analytics, or a related field, or an equivalent combination of education and relevant professional experience
- 8+ years of experience in data engineering, data management, master data management, or related disciplines, including hands-on pipeline and integration development
- Hands-on experience with PySpark, SQL, Delta Lake, Databricks Workflows, real-time and batch ETL, and API integrations
- 3+ years of experience leading data governance or master data management initiatives
- Experience establishing master records, data ownership models, and enterprise data standards
- Hands-on experience with Databricks and Unity Catalog in production environments
- Strong understanding of data quality, data modeling, entity resolution, and data access controls
- Experience partnering with business stakeholders to implement data governance practices
- Knowledge of data privacy, regulatory requirements, and information security principles
- Strong communication, collaboration, and stakeholder management skills
- Advanced degree in Information Systems, Data Analytics, or a related discipline (preferred)
- Databricks Data Engineer Associate or Professional certification, Certified Data Management Professional (CDMP) designation, or comparable industry certification (preferred)
- Experience in financial services, wealth management, or another regulated industry (preferred)
- Familiarity with Salesforce Financial Services Cloud, Orion, or Addepar (preferred)
- Experience with enterprise AI governance (preferred)
- Experience integrating and standardizing data following acquisitions (preferred)
Benefits:
- Fully remote work arrangement
- Limited travel for training, team meetings, or other business-related activities
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