Multiple Job Openings: Local Profiles Only: Business Intelligence / Python Developer, AWS / Java / Python Data Engineer, Data Engineer - Databricks / AWS

We have multiple immediate openings for skilled professionals on W2: Data Engineering, Python Development, and Cloud technologies.

Please review the opportunities below and share your interest.

1. Business Intelligence / Python Developer
   Location: Tampa, FL (Local Profiles Only)
   Experience: 8–12 Years
   Mode: 5 Days Onsite
   Primary Skills: Python, Business Intelligence, Data Visualization, Databases, ETL

Job Description:

• Develop and maintain Python-based applications, scripts, and APIs

• Build end-to-end data pipelines from various sources (APIs, DBs, SharePoint)

• Optimize data models and manage BAU data refresh pipelines

• Handle production issue resolution and performance monitoring

• Support ad-hoc analysis and maintain enhancement backlog

Qualifications:

• Bachelor’s degree in Computer Science or related field

• 3+ years developing Python-based applications

• Advanced SQL and ETL experience

• Knowledge of JIRA, SDLC, and CI/CD processes

2. AWS / Java / Python Data Engineer
   Location: Wilmington, DE (Local Profiles Only)
   Experience: 6–12 Years
   Mode: 5 Days Onsite
   Primary Skills: AWS, Java, Python, Big Data
   Nice to Have: Snowflake, Databricks

Responsibilities:

• Acquire and manage data from multiple sources

• Transform ETL logic to cloud platforms (AWS, Databricks)

• Implement and enhance software components using OOP and functional programming

• Ensure data quality, security, and consistency

• Hands-on experience in system design, development, testing, and operational stability
  
  
  

3. Data Engineer Databricks / AWS
   Location: Boston / Jersey City (Local Profiles Only)
   Experience: 8–12 Years
   Mode: 5 Days Onsite
   Skills: Python, Databricks, AWS Glue, PySpark, Data Lakes/Warehouses

Responsibilities:

• Design, develop, and maintain scalable ETL pipelines and workflows

• Build and optimize data lakes and warehouses using AWS platforms

• Automate data engineering tasks and implement CI/CD best practices

• Collaborate with analysts, scientists, and business teams to deliver reliable datasets

• Monitor and optimize pipeline performance and ensure data governance