Data Engineer (contract) w2 only! - Hybrid

Location: New York, NY - Hybrid3 Days a week onsite
Relocation: No
Employment Type: Contract – 6 months

REQUIRED: Previous hands-on experience in the Financial or Banking industry, capable of hitting the ground running and quickly building scalable data solutions. The ideal candidate will have a strong background in Azure Cloud.


Must have:

• Proficiency in Python: Strong experience in Python programming, particularly in developing ETL processes and data manipulation.
• Experience with Azure Cloud: Hands-on knowledge of Microsoft Azure services, including Azure Data Factory, Azure Databricks, Azure Storage, and Azure Virtual Machines.
• ETL Development: Ability to design and implement efficient ETL workflows to extract, transform, and load data from various sources.
• Data Governance and Compliance: Understanding of data governance principles, data quality management, and experience ensuring compliance with financial regulations (e.g., GDPR, CCPA).
• Data Pipeline Design: Experience in architecting scalable and flexible data pipelines, with a focus on performance optimization.
• Data Quality Assurance: Skills in implementing data quality checks and monitoring to maintain data integrity throughout the pipeline.
• Financial Services Experience: Previous experience working in the banking or financial services industry, understanding specific data handling and compliance challenges.
• Agile Methodologies: Ability to work effectively in a cross-functional Agile team, adapting to fast-paced project requirements.
• Communication Skills: Strong collaboration skills to work with stakeholders and teams, translating business requirements into technical solutions.

Job Requirements

• Python ETL: The ideal candidate should have strong proficiency in Python programming language and experience in Extract, Transform, Load (ETL) processes. They should be able to design and develop efficient ETL workflows to extract data from various sources, transform it as per business requirements, and load it into target systems.
• Azure Experience: The candidate should have hands-on experience working with Microsoft Azure cloud platform. They should be familiar with Azure services and tools and have a good understanding of Azure architecture and best practices.
• Azure Data Factory, DataBricks, Azure Storage, and Azure VM: The candidate should have practical experience with Azure Data Factory, DataBricks, Azure Storage, and Azure Virtual Machines. They should be able to design and implement data pipelines using Azure Data Factory, perform data transformations and analytics using DataBricks, and manage data storage and virtual machines in Azure.
• Data Governance, Data Quality, and Controls: The candidate should have a strong understanding of data governance principles, data quality management, and data controls. They should be able to implement data governance frameworks, establish data quality standards, and ensure compliance with data regulations and policies.
• Implementing alerts and notifications for batch jobs: The candidate should have experience in setting up alerts and notifications for batch jobs. They should be able to configure monitoring and alerting mechanisms to ensure timely identification and resolution of issues in batch job execution.