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Job
Title: Sr. Snowflake Data Engineer
Location: Jersey
City, NJ – 4 Days onsite (Local Candidate)
Visa:
H1b
Rate: $60/hr
on C2C
Need PP
Number to check i94 and TH
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.
Required
Skills & Qualifications:
- 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.
Thanks & Regards,
Sagar Agrawal
Sr. Recruiter