• Lead Data Integration Engineer

    Raymond James Financial, Inc. (St. Petersburg, FL)


    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.