Job description

Position Summary: Responsible for leading Data Engineering teams delivering enterprise data platforms and products using Databricks, Delta Lake, CDC, LakeFlow, cloud-native architectures, and modern data governance practices. Establishes engineering standards, drives platform modernization, leads enterprise data modernization initiatives, supports privacy and de-identification initiatives, enables Data Governance, Data Management and analytics capabilities, and partners across business and technology organizations to deliver scalable, secure and compliant data solutions. Responsibilities: • Manage and develop Data Engineering teams focused on Databricks and enterprise data platforms. • Define standards for Landing, Bronze, Silver and Gold data architecture layers. • Lead implementation of CDC, LakeFlow, streaming, batch and API integration patterns. • Drive enterprise data quality, lineage, metadata, observability and catalog capabilities. • Partner with Data Governance, Privacy, Security, Risk, Compliance and Records Management teams. • Lead data retention, de-identification, masking and privacy initiatives. • Lead enterprise data modernization initiatives, platform transformation programs, and legacy technology rationalization efforts. • Evaluate and implement modern cloud technologies and vendor solutions. • Provide architectural guidance and executive-level recommendations. • Lead Agile planning, staffing, mentoring, budgeting and performance management. • Directly manages Data Engineers and technical resources. Responsible for hiring, coaching, performance management and career development. • Ensure solutions comply with company policies and regulatory requirements. Requirements: • Databricks, Delta Lake, Unity Catalog, dbt and Lakehouse architecture expertise. • Strong experience with Python, SQL, Spark and large-scale data processing. • Knowledge of CDC, streaming, APIs, REST, GraphQL, JSON and XML. • Experience with Azure cloud platforms and cloud-native engineering practices. • Understanding of Data Governance, Data Management, metadata and data quality frameworks. • Experience with CI/CD, DevOps and Infrastructure as Code principles. • Strong leadership, communication and stakeholder management skills. • Proven experience leading data engineering efforts that enable AI, machine learning, or generative AI solutions, ensuring scalable, secure, and high-quality data foundations for analytics and model training. • 7+ years of Data Engineering experience with enterprise data platforms. • 3+ years leading technical teams. • Experience with Databricks, Spark and modern cloud data ecosystems required. • Removed legacy requirements including Visual Studio 2013/2015, SSIS-centric ETL development and SQL Server-focused architecture. • Bachelor degree preferred or equivalent experience. • Mortgage and financial services experience preferred. Why work for #teamloanDepot: • Work with other passionate, purposeful, and customer-centric team members. • Inclusive, diverse, and collaborative culture where people from all backgrounds can thrive. • Extensive internal growth and professional development opportunities including tuition reimbursement. • Comprehensive benefits package including Medical/Dental/Vision. • Wellness program to support both mental and physical health. • Generous paid time off options to support work-life balance. About loanDepot: loanDepot (NYSE: LDI) is a digital commerce company committed to serving its customers throughout the home ownership journey. Since its launch in 2010, loanDepot has revolutionized the mortgage industry with a digital-first approach that makes it easier, faster, and less stressful to purchase or refinance a home. Today, loanDepot enables customers to achieve the American dream of homeownership through a broad suite of lending and real estate services that simplify one of life's most complex transactions. With headquarters in Southern California and offices nationwide, loanDepot is committed to serving the communities in which its team lives and works through a variety of local, regional, and national philanthropic efforts. Base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay for this role is between $149,000 and $204,500. Your base pay will depend on multiple individualized factors, including your job-related knowledge/skills, qualifications, experience, and market location. We are an equal opportunity employer and value diversity in our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Requirements

Must-haves

Manage and develop Data Engineering teams focused on Databricks and enterprise data platforms.
Define standards for Landing, Bronze, Silver and Gold data architecture layers.
Lead implementation of CDC, LakeFlow, streaming, batch and API integration patterns.
Drive enterprise data quality, lineage, metadata, observability and catalog capabilities.
Partner with Data Governance, Privacy, Security, Risk, Compliance and Records Management teams.
Lead data retention, de-identification, masking and privacy initiatives.
Lead enterprise data modernization initiatives, platform transformation programs, and legacy technology rationalization efforts.
Evaluate and implement modern cloud technologies and vendor solutions.
Provide architectural guidance and executive-level recommendations.
Lead Agile planning, staffing, mentoring, budgeting and performance management.
Directly manages Data Engineers and technical resources. Responsible for hiring, coaching, performance management and career development.
Ensure solutions comply with company policies and regulatory requirements.
Databricks, Delta Lake, Unity Catalog, dbt and Lakehouse architecture expertise.
Strong experience with Python, SQL, Spark and large-scale data processing.
Knowledge of CDC, streaming, APIs, REST, GraphQL, JSON and XML.
Experience with Azure cloud platforms and cloud-native engineering practices.
Understanding of Data Governance, Data Management, metadata and data quality frameworks.
Experience with CI/CD, DevOps and Infrastructure as Code principles.
Strong leadership, communication and stakeholder management skills.
Proven experience leading data engineering efforts that enable AI, machine learning, or generative AI solutions, ensuring scalable, secure, and high-quality data foundations for analytics and model training.
7+ years of Data Engineering experience with enterprise data platforms.
3+ years leading technical teams.

Nice-to-haves

Bachelor degree preferred or equivalent experience.
Mortgage and financial services experience preferred.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

apiagilepythonsqlrestgraphqlazureci/cdaimachine learning

Platform: jobvite
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

Paid Time Off

Wellness

Professional Development