CRE Data and Analytics Engineer (with DevOps Experience)

• Location: South Bay, California
• $125000 base salary
• Remote: Remote
• Type: Direct Hire
• Job #1602
• Salary: $125,000 - $150,000

Title: CRE Data and Analytics Engineer (with DevOps Experience)

Industry: Financial Services – Investment Management

Location: South Bay – Hybrid

Overview: Pacific Executive Search has been engaged on a search for a CRE Data and Analytics Engineer with DevOps Experience. In this role, you will take on new responsibilities in designing and optimizing data solutions for commercial real estate lending, all while collaborating with cross-functional teams in the vibrant South Bay area. You can expect significant opportunities for career growth as you enhance your technical skills and contribute to innovative financial modeling and analytics initiatives.

Description:

Responsibilities

• Data Engineering & Analytics:
  • Develop and sustain sophisticated underwriting models, cash flow projections, and fund/portfolio analyses utilizing Excel (VBA, Power Query), SQL, and Python.
  • Create and manage efficient data pipelines, ETL processes, and integrations within Microsoft Azure and SQL Server to handle loan, asset, portfolio, and fund-level data.
  • Design and oversee Tableau dashboards and Excel reporting tools to provide real-time insights into CRE assets, portfolio performance, and credit risk.
  • Establish best practices for data quality, security, and compliance, ensuring the integrity and reliability of financial and operational data.
• Workflow Automation & Application Development:
  • Develop automated workflows for underwriting, portfolio/fund modeling, and risk evaluation to minimize manual tasks and enhance accuracy.
  • Create internal web applications and APIs using Python, JSON, Power Apps, n8n, and other low-code/AI platforms.
  • Consolidate financial modeling and reporting by integrating data from third-party CRE platforms, loan servicing systems, CRMs, and fund accounting tools.
• DevOps & Infrastructure:
  • Establish and maintain continuous integration and deployment (CI/CD) workflows (Azure DevOps, GitHub Actions) for reliable, test-driven releases.
  • Utilize Docker/Kubernetes for secure and scalable deployment of analytics applications and data services.
  • Employ Terraform/ARM templates or similar tools for efficient provisioning and management of Azure resources.
  • Adhere to strict data security protocols, including encryption, access control, and compliance measures for sensitive financial information.
• Cross-Functional Collaboration:
  • Collaborate with underwriters, asset/fund managers, and risk teams to convert CRE and fund-modeling needs into technical solutions.
  • Deliver complex analytics, forecasts, and recommendations regarding underwriting decisions, portfolio performance, fund returns, and credit risk to business leaders.
  • Stay updated on emerging trends in AI, ML, and automation that can improve fund modeling, real estate analytics, and operational efficiency.

Qualifications

• Technical Expertise:
  • In-depth knowledge of CRE lending, fund/portfolio modeling, and advanced financial modeling techniques.
  • Advanced proficiency in MS Azure (Data Factory, SQL DB), SQL, Tableau, Excel (VBA, Power Query), ETL processes, and data modeling.
  • Proven experience in programming with Python, JSON, JavaScript, Git/GitHub, VS Code, and low-code AI frameworks for application development.
  • Practical experience with CI/CD, containerization (Docker/Kubernetes), and infrastructure-as-code (Terraform/ARM templates).
• Soft Skills & Business Acumen:
  • Capability to interpret intricate CRE and fund modeling requirements, aligning technical solutions with financial strategies and performance goals.
  • Excellent communication skills for conveying technical concepts to cross-functional teams (finance, credit, operations).
  • Self-motivated with the ability to manage multiple projects in a dynamic environment.
• Preferred Experience:
  • Familiarity with CRE loan servicing systems, underwriting software, or asset/fund management platforms.
  • Experience in credit risk modeling, fund performance analysis, or structured finance.
  • Knowledge of CRM automation, alternative lending technologies, and advanced CRE data sources.