Data Engineer with SQL, python, and finance experience

Data Engineer with SQL, python, and finance (investment/capital markets) experience  || H1B and USC || H4 || TN

Location: New York, NY  – 5 days onsite

Duration: 6 months

Contract To Hire

Job Description

Role: Data Engineer Location- New York, NY  

JD- Must have finance (investment/capital markets) experience  

Job Description :   

·         We are looking for an experienced Data Engineer with expertise in SQL, python, and strong data modeling skills.  

·         In this role, you will be at the heart of our data ecosystem, designing and maintaining data pipelines and models that drive decision-making across the organization.

·         You will play a key role in ensuring data quality, building scalable systems, and supporting cross-functional teams with clean, accurate, and actionable data.   Key Skills: Python, SQL, Snowflake, Pandas, Azure ADF ETL, Data pipelines Behavioral Competencies: Good communication (verbal and written) Experience in managing client stakeholders  

Qualifications : 

·         Bachelor's or master’s degree in computer science, Engineering, or a related field.

·         3+ years of experience in data engineering, with a strong background in building and maintaining data pipelines and ETL processes.

·         Strong proficiency in SQL and experience with relational databases. Proficiency with Python. In-depth knowledge of data modeling, ETL processes, and data integration techniques.

·         Experience with data warehousing solutions.

·         Experience with web-scraping.

·         Strong problem-solving skills and the ability to work independently and as part of a team.

·         Excellent communication skills, with the ability to collaborate effectively with cross-functional teams.  

Responsibilities:  

·         Design, develop, and maintain scalable and efficient data pipelines and ETL processes.

·         Experience with python, SSIS, PDI, Azure Data Factory or other ETL tools.

·         Improve data ETL pipeline and build tools to analyze new data efficiently.

· Collaborate with data scientists/analysts, and stakeholders to understand data requirements and translate them into technical specs.

·         Build technologies to bolster research & trading efficiency.

·         Implement best practices for data quality, consistency, and governance across various data sources and systems.

·         Implement best practices in Data Engineering to drive innovation and enhance our platform as we scale.

·         Manage day-to-day operations in a fast-paced environment.

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