Lead Data Engineer

Reprise Financial is on a mission to simplify the financial journey for customers through technology and a customer-first approach. They are seeking a Lead Data Engineer to design, develop, and maintain data architecture and ETL processes that support data movement and integration across multiple systems.

Responsibilities:

• Collaborate with and support cross-functional teams to ensure accurate and efficient data flow across systems
• Defines architectural strategy across programs or domains, handles highest-risk, highest-value solutions, influences enterprise standards and vendor selection, and advises leadership on technical direction
• Leads architecture for large, complex or cross-domain solutions, mentors junior architects and engineers, defines architecture standards and patterns, manages technical risk and architectural debt, partners closely with product owners and program leaders, and influences roadmap and platform strategy
• Develop, integrate, test, deploy and maintain scalable ETL pipelines and workflows using tools such as SSMS, SSIS, Azure Data Factory, and Fabric Data Factory
• Integrate data utilizing industry standard file formats such as flat files, Excel, Oracle, SQL Server, XML, XSL, and JSON. Get/Post data using SFTP and REST APIs
• Use database design and development best practices to design and maintain robust database systems involving development, implementation, and optimization of various DB objects such as Tables, Views, Stored Procedures, and Functions
• Assemble large, complex data sets that meet functional / non-functional business requirements
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc
• Develop and perform unit tests; maintain up-to-date code in source control
• Collaborate on code reviews and adhere to change management processes to deploy changes to production systems
• Troubleshoot issues reported by users and perform root cause analysis for production issues with minimal guidance
• Document ETL processes, data flows, and system integrations for audit and compliance purposes. Develop user guides and reference documents
• Use Agile best practices to enhance team efficiency and product delivery. Leverage JIRA / Azure Boards for writing detailed user stories, breakdown complex projects into manageable tasks to ensure smooth sprint execution
• Continuously learn about the business and the data that supports it

Requirements:

• 8+ years of experience in a Lead Data Engineer, Data Engineer, and/or Data Architect role
• Experience one or more Data Architecture Domains: BI Architect, Analytics Architect, Data Architect, Data Integration/ETL Architect, Data Governance Architect, and/or Cloud Architect
• Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, or relevant technical degree
• Strong knowledge of data warehouse and lakehouse concepts
• Strong analytic skills related to working with structured, semi-structured, and unstructured datasets
• Experience with cloud migration from on-prem or from another cloud platform
• Experience with cloud data platforms like Microsoft Azure, Microsoft Fabric, Amazon Web Services, Google Cloud Platform, and Snowflake, as well as, Microsoft SQL Server
• Proficient with building ETL processes using tools such as SSMS, SSIS, Azure Data Factory, and Fabric Data Factory
• Proficient with SQL, Spark SQL, PySpark, and Python working with relational databases
• Proficient in T-SQL, Stored Procedures, and Functions using REST APIs
• Experience performing ad-hoc and root cause analysis on internal and external data, and processes to answer specific business questions
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management
• Experience supporting and working with cross-functional teams in a dynamic environment
• Experience maintaining code base using source control and Dev-Ops including CI/CD
• Experience developing and maintaining technical and non-technical documentation
• Data governance experience involving implementation and management of data cataloging, metadata management, and data lineage tracking
• Excellent verbal and written communication skills
• Good interpersonal skills with proven problem-solving abilities
• Experience in the finance industry, specifically in loan origination and servicing
• Experience developing and maintaining technical and non-technical documentation. Confluence experience is a plus
• Knowledge of financial data structures, including loan origination, servicing, payments, and collections