Senior Data Analyst (Real Estate Lending Systems)

Overview

Partner with business stakeholders and other analysts to understand business data needs, capture data requirements, and perform data transformation, integration, and storage. Provide inputs for complex data architecture and perform ETL on large data sets to support departmental and organizational objectives. Work under minimal supervision and use complete understanding of business needs and objectives to support projects that have impact on the achievement of operational goals. Advanced skill set and proficiency with data transformation practices, query languages, script languages, ETL pipelines and analysis techniques.

Responsibilities

• Develop and maintain data pipelines, workflows, and APIs using Data Factory, MongoDB, and SQL Server Integration Services
• Work with leadership to help determine data framework and architecture for efficient and optimized processes
• Understand data governance concepts to help tag metadata, secure personal information and comply with regulations
• Understand and be familiar with REL specific data sets
• Work with technology organization and business end-users to understand data and analysis needs and develop technical requirements including data definitions, business rules, and data quality requirements; conduct data UAT, and data accuracy, validation, integrity research
• Ensure compliance with deliverable reporting requirements by performing quality data audits and analysis
• Identify and compile data sets using a variety of transformation tools to help predict, improve, and measure the success of key business-to-business outcomes
• Analyze and resolve complex data quality issues, utilizing advanced data profiling, cleansing, and monitoring techniques to maintain data integrity and reliability
• Clean and organize raw data and generate data tables in support of business intelligence and data science projects
• Build working relationships with team members and subject matter experts
• Lead small projects and initiatives

• 5-7 years of experience in data analysis and reporting
• Complete knowledge and understanding of business area/specialization
• Skill in data manipulation and scripting languages such as SQL, Python, or R, as well as advanced data cleaning and preprocessing techniques and tools
• Skill in data transformation tool such as Data Factory and SQL Server Integration Services
• Skill in data architecture frameworks such as SQL Server, Azure, Cosmos and MongoDB
• Proficiency in Data Governance best practices and policies
• Effective skill with ETL tools and techniques, data cleaning, and other analytical techniques required for data usage
• Advanced skill interpreting, extrapolating and interpolating data for statistical research and modeling
• Knowledge of various data structures and ability to extract data sources (e.g., PySpark, PowerBI)
• Strong understanding of data governance principles and practices
• Bachelor's Degree in Statistics, Mathematics, Computers Science, Engineering, or degrees in similar quantitative fields