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.

• 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 Dev Ops 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.

• 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 Power Shell/Shell scripting, for automation, data manipulation, and pipeline development.
• Cloud & Dev Ops (Desired):
  Familiarity with cloud platforms (e.g., Azure Data Factory, AWS Glue, Google Cloud) and experience implementing CI/CD pipelines and Dev Ops 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.