Lead Data Integration Engineer

Job Description _This position follows our hybrid workstyle policy: Expected to be in a Raymond James office location a minimum of 10-12 days a month._ _Please note: This role is not eligible for Work Visa sponsorship, either currently or in the future._ Responsibilities: + Deep expertise in Microsoft SQL Server, SSIS, and SQL development. + Strong proficiency in writing and optimizing complex stored procedures, functions, and packages. + Hands-on experience with Python for data manipulation, automation, and pipeline development. + Familiarity with Oracle databases and PL/SQL development is required for cross-platform data integration. + Experience in implementing CI/CD pipelines and DevOps practices for data solutions. + Understanding data warehousing concepts, ETL methodologies, and data modeling techniques. + Experience with Unix and Shell scripting + Experience with job scheduler tools such as BMC Control-M + Proven track record working in both waterfall and agile SDLC frameworks + Knowledge of the Financial Services industry including middle and back-office functions + Experience in collaborating with business counterparts to understand detailed requirements + Excellent verbal and written communication skills + Produce and maintain detailed technical documentation for all development efforts. Skills: + MS SQL Server & SQL Proficiency: Deep expertise in writing and optimizing complex SQL queries, stored procedures, functions, and triggers is fundamental. + SSIS Expertise: In-depth knowledge of designing, developing, deploying, and maintaining ETL (Extract, Transform, Load) processes and packages using SQL Server Integration Services (SSIS). This includes robust error handling and logging mechanisms. + ETL & Data Warehousing: Strong understanding of ETL methodologies, data warehousing concepts (e.g., Kimball methodology, star schemas), and data modeling techniques (normalization/denormalization). + Performance Tuning: Ability to identify, investigate, and resolve database and ETL performance issues, including capacity and scalability planning. + Programming Languages: Proficiency in additional programming/scripting languages, such as Python or PowerShell/Shell scripting, for automation, data manipulation, and pipeline development. + Cloud & DevOps (Desired): Familiarity with cloud platforms (e.g., Azure Data Factory, AWS Glue, Google Cloud) and experience implementing CI/CD pipelines and DevOps practices for data solutions is a strong advantage. + Exposure to streaming technologies such as Kafka is a plus. + Experience in financial services or enterprise-scale applications is preferred. + Excellent communication, analytical, and problem-solving skills.

Created: 2026-03-07