Lead Data Engineer, Master Data Management

Clearstead

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

Posted 10/31/2026full-timeRemote • United StatesSenior💰 $145,000 - $180,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data engineering, including the design and implementation of scalable data pipelines, data governance frameworks, and data quality standards. Proficient in leveraging tools like Databricks and PySpark to enhance data processing and integration across various environments.

Highest-signal resume keywords

Data EngineeringDatabricks Platform ManagementData Governance LeadershipETL DevelopmentData Quality Assurance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PySparkSQLDelta LakeETLAPI IntegrationsData ModelingEntity ResolutionData Access ControlsData IntegrationData Processing

Soft Skills

CommunicationCollaborationStakeholder Management

Tools & Technologies

DatabricksUnity CatalogSalesforce Financial Services CloudOrionAddepar

Certifications & Qualifications

Databricks Data Engineer AssociateCertified Data Management Professional (CDMP)

Industry Keywords

Data ManagementMaster Data ManagementFinancial ServicesWealth ManagementRegulatory Compliance

Tech Stack

Tools & technologies

CloudETLPySparkSQLUnity

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

Fully remote work arrangement
Limited travel for training, team meetings, or other business-related activities