Ab Initio Engineer

Title: Ab Initio Engineer Location: Hartford, CT (Hybrid) Only Local) Duration: Long Term Contract

Job description: •Work location: Hartford, 06183 •Will this role work remote/In Office/Hybrid (in office & remote) - Hybrid (must be in office for 3 days) •Does the resource have to be Local: - Yes •"Must-have” skills for this role: 1. Ab Initio 2. SAS 3. Databricks •Years of experience required for each skill: 4-6 years and need TL •What are some “nice-to-have” skills : 1. AWS Cloud 2. 3.

•Job description

Client & Project: We are seeking a new talent to join the team where you will have the opportunity to collaborate in the project. The client is a company that provides a wide range of insurance products and services to individuals and businesses.

Here's a quick overview of the skillset we're looking for:

• Ab Initio
• Python
• AWS Cloud technology
• SQL ( Teradata , SQL Server and Client)
• Databricks
• SAS

•Responsibilities: As a Data Engineer, you will be responsible for designing, developing, and maintaining data solutions for data generation, collection, and processing. Your day-to-day activities will include creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across systems. You are expected to be a subject matter expert, collaborate and manage the team to perform effectively. You will be responsible for team decisions, engage with multiple teams, and contribute to key decisions while providing solutions to problems for your immediate team and across multiple teams. Expert proficiency in Ab Initio is required. Expert proficiency in SAS Analytics is recommended. Expert proficiency in AWS Compute, Data Engineering, Databricks Platform, and Teradata SQL is suggested. •Develop innovative data solutions that enhance data processing efficiency. • Collaborate with cross-functional teams to identify and implement best practices in data management. •Monitor and optimize data pipelines for performance and reliability. •Conduct regular data quality assessments and implement necessary improvements. • Stay updated with industry trends and emerging technologies to continuously improve data engineering practices.