Senior Data Engineer - AI & Data Pipelines (Hybrid NYC)

CloudIngest INC

New York (NY)

Hybrid

USD 76,000 - 83,000

Part time

43 hours ago
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Job summary

CloudIngest INC is seeking an experienced Data Engineer to design and maintain reliable data pipelines on-site in Manhattan, NY, with a hybrid work arrangement (3 days in-office). You will collaborate with the Data Architect and AI team to deliver high-quality data for analytics and AI solutions.

The role demands 8–12 years of experience, strong SQL/Python, and hands-on work with Airflow/ADF, Spark, and cloud data services.

Qualifications

  • 5+ years in data engineering (hands-on).
  • Strong SQL and Python (or Scala) skills.
  • Experience with Airflow or Azure Data Factory for orchestration.
  • Hands-on experience with cloud data services and Spark.
  • Understanding of data warehousing and lakehouse concepts.
  • Familiarity with Git, CI/CD, and infrastructure-as-code.
  • Experience supporting ML/AI data needs is a plus.

Responsibilities

  • Design, build, and optimize batch and streaming data pipelines.
  • Implement data models and transformations defined by the Data Architect.
  • Ingest and integrate data from multiple source systems and APIs.
  • Implement data quality checks, monitoring and alerting.
  • Optimize performance and cost of data workloads.
  • Collaborate with AI Developers and analysts to provision datasets.
  • Maintain documentation, version control and CI/CD for data code.
  • Work with offshore data engineers on knowledge transfer and delivery.

Skills

SQL
Python
Spark
Airflow
Azure Data Factory
CI/CD

Tools

Git
CI/CD

Job description

CloudIngest INC is seeking an experienced Data Engineer to design and maintain reliable data pipelines on-site in Manhattan, NY, with a hybrid work arrangement (3 days in-office). You will collaborate with the Data Architect and AI team to deliver high-quality data for analytics and AI solutions.

The role demands 8–12 years of experience, strong SQL/Python, and hands-on work with Airflow/ADF, Spark, and cloud data services.

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