Job Title: Senior Data Engineer
Location: Dallas, TX (Onsite)
Employment Type: Full-time
Job Summary
We are seeking an experienced Senior Data Engineer to support a large-scale enterprise data platform modernization and system migration initiative. This role will be responsible for designing, building, and optimizing scalable data pipelines, data warehouses, and cloud-based data platforms that enable trusted analytics and AI-driven decision-making.
The ideal candidate will have extensive experience with Python, SQL, ETL/ELT development, Snowflake, BigQuery, dbt, Airflow, and cloud data platforms. Experience within the Mortgage Industry, particularly in mortgage servicing, settlements, remittances, and servicing workflows, is highly preferred.
In addition to hands-on data engineering, this role requires collaboration with business stakeholders, architects, data scientists, and engineering teams to support platform migration, data validation, governance, and successful project delivery.
Key Responsibilities
Data Engineering & Pipeline Development
- Design, develop, and maintain scalable ETL/ELT pipelines for enterprise data integration.
- Build high-performance, reusable data pipeline frameworks using Python and SQL.
- Develop and optimize enterprise data warehouses and cloud-native data platforms.
- Implement robust data integration solutions supporting analytics, reporting, and AI initiatives.
- Optimize data processing performance, scalability, and reliability.
Data Modeling
- Design and implement scalable data models, including:
- Star Schema
- Snowflake Schema
- Data Vault
- Establish data modeling standards aligned with enterprise architecture.
- Ensure consistency, scalability, and performance across data solutions.
Cloud Data Platforms
- Build and support enterprise cloud data platforms using:
- Snowflake
- Google BigQuery
- Databricks
- Amazon Redshift
- Microsoft Fabric
- Collaborate with Cloud Architects and Platform Engineers on cloud-native solutions.
- Support multi-cloud data engineering initiatives across AWS, Azure, and Google Cloud Platform.
System Migration & Data Validation
- Support the technical execution of large-scale system migration projects.
- Build migration pipelines and validate migrated data.
- Perform reconciliation and data quality validation throughout migration activities.
- Collaborate with cross-functional teams during migration planning, testing, cutover, and post-production validation.
- Support stakeholder alignment and operational readiness throughout project execution.
Data Governance & Quality
- Implement data quality, validation, monitoring, and governance frameworks.
- Define and maintain data quality SLAs and operational monitoring standards.
- Support metadata management, data lineage, access controls, and compliance requirements.
- Ensure data integrity, security, and consistency across enterprise platforms.
Infrastructure & Automation
- Automate data platform deployments using Terraform or similar Infrastructure-as-Code (IaC) tools.
- Develop and maintain CI/CD pipelines for data engineering solutions.
- Drive automation and continuous improvement across engineering processes.
Leadership & Collaboration
- Partner with Product Managers, Business Analysts, Data Architects, and Data Scientists to deliver enterprise data solutions.
- Mentor junior engineers and promote engineering best practices.
- Lead technical discussions, solution design, and architecture reviews.
- Contribute to Agile planning, sprint execution, and cross-functional delivery.
Required Qualifications
- Bachelor''s degree in computer science, Information Technology, Engineering, or a related field.
- 8+ years of experience designing and implementing enterprise-scale data engineering solutions.
- Strong experience supporting enterprise data migration and modernization initiatives.
- Advanced expertise in SQL and enterprise data modeling.
- Strong programming experience with Python.
- Extensive experience designing and developing ETL/ELT pipelines.
- Hands-on experience with cloud data platforms including Snowflake, BigQuery, Databricks, Redshift, or Microsoft Fabric.
- Experience with orchestration tools such as Airflow, dbt, or Informatica.
- Strong understanding of cloud platforms (AWS, Azure, or Google Cloud Platform).
- Experience with Terraform or other Infrastructure-as-Code (IaC) tools.
- Strong knowledge of CI/CD processes for data platform deployments.
- Excellent communication and stakeholder management skills.
Preferred Qualifications
- Experience within the Mortgage Industry, including:
- Mortgage Servicing
- Asset-Backed Finance (ABF)
- Settlements
- Remittances & Cash Consolidation
- Servicing Workflows
- Experience leading enterprise system migration programs.
- Experience with Product or Program Management throughout the software development lifecycle.
- Experience working in Agile or hybrid delivery environments.
- Knowledge of enterprise data governance and compliance frameworks.
Required Technical Skills
Programming
Data Engineering
- ETL / ELT
- Data Modeling
- Star Schema
- Snowflake Schema
- Data Vault
- Data Warehousing
- Data Integration
Cloud Data Platforms
- Snowflake
- Google BigQuery
- Databricks
- Amazon Redshift
- Microsoft Fabric
Data Orchestration
- Apache Airflow
- dbt
- Informatica
Cloud Platforms
- AWS
- Microsoft Azure
- Google Cloud Platform (Google Cloud Platform)
Infrastructure & DevOps
- Terraform
- Infrastructure as Code (IaC)
- CI/CD
- Git
Analytics & Reporting
Data Governance
- Metadata Management
- Data Lineage
- Data Quality
- Data Validation
- Access Controls
- Compliance
Preferred Certifications
- Snowflake SnowPro Certification
- AWS Certified Data Analytics – Specialty
- Microsoft Azure Data Engineer Associate
- Google Cloud Professional Data Engineer
Core Competencies
- Enterprise Data Engineering
- Cloud Data Platform Architecture
- ETL/ELT Development
- Data Pipeline Optimization
- Data Warehouse Design
- Data Migration & Modernization
- Data Governance & Quality
- Infrastructure as Code (IaC)
- Agile Delivery
- Technical Leadership
- Cross-functional Collaboration
- Stakeholder Management
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