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Data Engineer with Cloud experience

SANSNew York, NY🇺🇸United StatesPosted Sep 6, 2026

Why This Role Stands Out

This hybrid Data Engineer role offers a fantastic opportunity to build and optimize scalable data pipelines using cutting-edge cloud technologies, contributing directly to SANS's analytics and machine learning initiatives. You'll thrive here if you have a strong background in Python, SQL, and cloud platforms, enjoy collaborating with diverse teams, and are eager to drive data innovation in a reputable organization. Apply now to leverage your skills and grow your career in a dynamic environment!

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
New York, NY, United States
Posted
1 week ago
OracleSQLSQL ServerAWSETLFlinkMachine LearningApacheApache SparkAzureGitGoogle CloudKafkaPythonRedshiftVaultdbt

Job Description

Please do not send your resume if you are not physically local to NYC/NJ as in-person interview is required.

Job Title - Data Engineer
Location - New York, NY (Hybrid)
Duration - 12+ Months

About the Role: We are looking for a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure that power our analytics and machine learning capabilities. You will work cross-functionally with data scientists, analysts, and product teams to ensure data is reliable, accessible, and performant across the organization.

Key Responsibilities:

  • Design, build, and maintain robust ETL/ELT pipelines to ingest, transform, and deliver data from diverse sources.
  • Develop and manage data warehouses and data lakes using cloud platforms such as AWS, Google Cloud Platform, or Azure.
  • Ensure data quality, integrity, and availability through monitoring, testing, and alerting frameworks.
  • Collaborate with data scientists and analysts to understand data needs and deliver optimized data models.
  • Optimize query performance and storage efficiency across large-scale distributed systems.
  • Define and enforce data governance best practices, including lineage, cataloging, and documentation.
  • Partner with engineering teams to integrate data infrastructure with production systems.
  • Continuously evaluate and adopt new tools and technologies to improve the data platform.

Required Qualifications

  • 5+ years of experience in data engineering, software engineering, or a related field.
  • Proficiency in Python for data processing and pipeline development.
  • Strong SQL skills and experience with databases (e.g., SQL Server, Oracle, Redshift).
  • Experience with big data technologies such as Apache Spark, Kafka, or Flink.
  • Hands-on experience with cloud platforms (AWS, Google Cloud Platform, or Azure) and their data services.
  • Familiarity with version control (Git) and CI/CD practices.
  • Solid understanding of data modeling concepts (star schema, data vault, etc.).
  • Strong analytical and problem-solving skills with a focus on data quality and reliability.

Nice to Have:

  • Experience with dbt (data build tool) for transformation and data modeling.
  • Knowledge of streaming data architectures and real-time processing.
  • Familiarity with data observability tools such as Monte Carlo or Great Expectations.
  • Exposure to machine learning workflows and feature engineering pipelines.
  • Experience working in a fast-paced startup or high-growth environment.

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