Senior Data Engineer

jps tech solutions • United State
Remote Visa Sponsorship
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AI Summary

We are looking for an experienced Senior Data Engineer to design, build, and deploy scalable data pipelines and backend data services. The ideal candidate will have 12+ years of hands-on experience in data engineering, with deep expertise in Snowflake data modeling, modern data engineering practices, and building reliable, high-performance data platforms to support analytics and business intelligence.

Key Highlights
Design, develop, and deploy end-to-end data pipelines for large-scale data processing
Perform Snowflake data modeling, including schema design, optimization, and performance tuning
Implement ELT/ETL processes for structured and semi-structured data sources
Key Responsibilities
Design, develop, and deploy end-to-end data pipelines for large-scale data processing
Build and maintain backend data services and APIs to support data consumption
Perform Snowflake data modeling, including schema design, optimization, and performance tuning
Technical Skills Required
Snowflake SQL Python Java Airflow Azure Data Factory AWS Azure GCP Git DevOps
Benefits & Perks
Remote work
W2-Contract Only
Visa sponsorship for H4-EAD, Green Card Holder, GC-EAD, U.S. Citizen, L2s, L2-EAD, or J2-EAD
Nice to Have
Experience with streaming data technologies (Kafka, Kinesis)
Exposure to dbt or other modern transformation frameworks
Background in large-scale enterprise or regulated environments

Job Description


Job Category: Data Engineer

Job Type: Remote

Job Location: California San Francisco

Compensation: Depends on Experience

W2: W2-Contract Only; Kindly note that applications on a C2C basis will not be considered for this role.

Eligible Visa: GC GC-EAD H4 EAD L2S U.S. Citizen (USC)

Job Description

Visa Requirement:

This position is open only to candidates authorized to work in the United States under the following visa categories: H4-EAD, Green Card Holder, GC-EAD, U.S. Citizen, L2s, L2-EAD, or J2-EAD. No other visa types are eligible for this role.

Job Overview

We are looking for an experienced Senior Data Engineer to design, build, and deploy scalable data pipelines and backend data services. The ideal candidate will have 12+ years of hands-on experience in data engineering, with deep expertise in Snowflake data modeling, modern data engineering practices, and building reliable, high-performance data platforms to support analytics and business intelligence.

Key Responsibilities

Design, develop, and deploy end-to-end data pipelines for large-scale data processing.

Build and maintain backend data services and APIs to support data consumption.

Perform Snowflake data modeling, including schema design, optimization, and performance tuning.

Implement ELT/ETL processes for structured and semi-structured data sources.

Optimize data storage, query performance, and cost efficiency in Snowflake.

Ensure data quality, reliability, security, and governance across all pipelines.

Collaborate with Data Scientists, Analysts, and business stakeholders to understand and meet data needs.

Implement monitoring, logging, and alerting for data pipelines to ensure reliability.

Support CI/CD pipelines for efficient and consistent data engineering deployments.

Document data flows, architecture, and best practices to support team knowledge sharing.

Required Skills & Qualifications

12+ years of experience in Data Engineering or related roles.

Strong hands-on experience with Snowflake, including data modeling, performance tuning, and security.

Expert-level SQL Skills And Experience With Data Transformation Techniques.

Proficiency in Python and/or Java for backend data processing.

Proven experience building scalable ETL/ELT pipelines.

Knowledge of data orchestration tools such as Airflow, Azure Data Factory, or equivalent.

Experience with cloud platforms (AWS, Azure, or GCP) for data solutions.

Familiarity with CI/CD pipelines, Git, and DevOps practices.

Strong problem-solving, analytical, and communication skills.

Nice To Have

Experience with streaming data technologies (Kafka, Kinesis).

Exposure to dbt or other modern transformation frameworks.

Background in large-scale enterprise or regulated environments.

Knowledge of data governance and metadata management tools.

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