Lead Data Engineer, Master Data Management

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and implement solutions for both real-time and batch data processing aimed at modeling, analytics, and reporting.

• Develop and sustain scalable data pipelines along with API integrations.

• Construct and oversee complex datasets.

• Create database applications and data integration layers utilizing database programming languages, ETL tools, and scripting languages.

• Establish and advocate for data engineering standards, documentation, coding practices, and technical best practices.

• Apply security measures and controls to safeguard enterprise data and code.

• Connect data across cloud, multicloud, and on-premises settings.

• Investigate and suggest improvements to database design, development practices, tools, and platform capabilities.

• Collaborate with data scientists and business teams regarding modeling, reporting, data processing, and visualization requirements.

• Troubleshoot issues related to data design, engineering, and integration.

• Develop and execute enterprise data governance policies, standards, and ownership frameworks.

• Create unified records for clients, households, legal entities, and accounts.

• Lead the processes of data matching, entity resolution, duplicate identification, and stewardship.

• Define business terms, data dictionaries, and certification standards.

• Design and implement automated data quality checks, reconciliation processes, and remediation protocols.

• Co-manage the Databricks platform, including Unity Catalog and data access controls.

• Provide second-line support for the Databricks platform.

• Monitor data integrity and address quality issues across enterprise systems.

• Support data integration and standardization efforts following acquisitions.

• Establish and facilitate cross-functional data ownership and governance forums.

• Standardize data definitions and address inconsistencies in collaboration with business leaders.

• Communicate findings regarding data quality, risks, and areas for improvement.

• Promote accountability for enterprise data quality and governance standards.

• Chair quarterly reviews of AI agents within the firm.

• Collaborate across wealth management, investments, operations, finance, compliance, and technology sectors.

⛳️ 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 fields, including practical experience in 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 projects.

• Experience in establishing master records, data ownership models, and enterprise data standards.

• Practical experience with Databricks and Unity Catalog in production settings.

• Solid understanding of data quality, data modeling, entity resolution, and data access controls.

• Experience collaborating with business stakeholders to implement data governance practices.

• Knowledgeable about data privacy, regulatory requirements, and information security principles.

• Strong skills in communication, collaboration, and stakeholder management.

• Advanced degree in Information Systems, Data Analytics, or a related field (preferred).

• Databricks Data Engineer Associate or Professional certification, Certified Data Management Professional (CDMP) designation, or similar 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 in integrating and standardizing data after acquisitions (preferred).

🏝️ Benefits

• Fully remote work arrangement.

• Limited travel for training, team meetings, or other business-related activities.