Need Snowflake Data Engineer in Jersey City NJ 4 Days onsite

[Recruiter IT]

Job Title: Sr. Snowflake Data Engineer

Location: Jersey City, NJ – 4 Days onsite role

Long Term Project

 

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Job Summary: We are seeking an experienced Senior Data Engineer with strong financial domain experience to design, build, and manage scalable data platforms. The ideal candidate will have deep hands-on expertise with Snowflake, dbt, Python, Airflow, Kubernetes, and SQL, along with a solid understanding of data architecture and design principles. This role requires someone who can work independently, take ownership of deliverables, and collaborate effectively with both technical and business stakeholders.

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Required Skills & Qualifications:

• 7–8+ years of hands-on experience in Data Engineering or related roles.
• Strong experience working in the financial services domain (banking, capital markets, risk, finance, or similar).
• Extensive hands-on experience with Snowflake in production environments.
• Strong expertise in SQL (complex queries, performance optimization, analytical patterns).
• Experience building and managing data transformations using dbt.
• Proficient in Python for data processing and orchestration.
• Hands-on experience with Apache Airflow for workflow orchestration.
• Working knowledge of Kubernetes and containerized deployments.
• Solid understanding of data modeling, data warehousing, and data architecture concepts.
• Experience working independently and owning end-to-end delivery.
• Strong problem-solving and analytical skills.

Key Responsibilities:

• Design, develop, and maintain robust, scalable, and high-performance data pipelines and data platforms.
• Architect and implement cloud-based data solutions with a strong focus on Snowflake.
• Build and manage transformation frameworks using dbt and SQL best practices.
• Develop and orchestrate batch and near real-time data workflows using Airflow.
• Containerize and deploy data workloads using Kubernetes where applicable.
• Support data modeling and design activities, including work on analytical data structures such as data marts.
• Contribute to modernization efforts, including migration of legacy on-premises databases (e.g., Oracle) to cloud data platforms.
• Ensure data quality, reliability, performance, and security across data pipelines.
• Collaborate with cross-functional teams including Data Architects, Analytics, Product, and Business stakeholders.
• Identify opportunities to improve development efficiency by leveraging modern tooling, automation, and AI-based agents and tools.
• Act as a senior individual contributor, independently managing tasks, priorities, and deliverables.
• Adhere to software engineering best practices, including version control, code reviews, documentation, and CI/CD.