Senior Data Engineer - Cloud Data Pipelines & Warehousing

Hudson Manpower; New Jersey; On-site; USD 140,000 - 200,000; Full time

Job summary

Hudson Manpower seeks a Senior Data Engineer with 8+ years of hands-on experience to design, develop, and maintain scalable data platforms, pipelines, and analytics solutions. You will work with Data Scientists, BI Developers, software engineers, and stakeholders to deliver reliable, secure data solutions for analytics and AI/ML initiatives.

Responsibilities include building scalable batch and real-time data pipelines, ETL/ELT workflows, complex SQL transformations, data warehousing, Spark, and

Qualifications

• Bachelor's or higher degree in CS/IT/Eng/Data Science.
• 8+ years of professional data engineering experience.
• Experience leading data engineering projects.
• Strong knowledge of cloud data warehouses and data lakehouse concepts.
• Proficient in Python and SQL.

Responsibilities

• Design and maintain scalable batch and real-time data pipelines.
• Build ETL/ELT workflows across multiple sources.
• Develop SQL queries, stored procedures, and data transformations.
• Implement data warehouses/lakes and lakehouses with modern models.
• Work with Spark, Kafka, and cloud platforms.
• Ensure data quality, governance, security, and observability.
• Mentor engineers and promote best practices.
• Collaborate with stakeholders to translate requirements.

Skills

Python

SQL

Data modeling

Data architecture

ETL/ELT

Distributed processing

Cloud platforms

Data governance

Mentoring

Education

Bachelor's degree in CS/IT/Eng/Data Science

Master's degree in CS/IT/Eng/Data Science

Tools

Apache Airflow

Azure Data Factory

AWS Glue

dbt

Informatica

Talend

SSIS

Kafka

Kinesis

Databricks

Snowflake

Redshift

BigQuery

Job description

Hudson Manpower seeks a Senior Data Engineer with 8+ years of hands-on experience to design, develop, and maintain scalable data platforms, pipelines, and analytics solutions. You will work with Data Scientists, BI Developers, software engineers, and stakeholders to deliver reliable, secure data solutions for analytics and AI/ML initiatives.

Responsibilities include building scalable batch and real-time data pipelines, ETL/ELT workflows, complex SQL transformations, data warehousing, Spark, and