Data Engineer Level 2

Manpower
Cincinnati, OH, United States
25 days ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
$145,600.0 - $156,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Automation of Tests Microsoft Azure Big Data BigQuery Cloud Computing Information Engineering Extract Transform Load (ETL) Data Systems Distributed Computing Environment Python (Programming Language) NoSQL
+13 more
Systems Development Life Cycle Standard Sql SQL Databases Data Streaming Google Cloud Cloud Platform System Performance Testing Feature Engineering Apache Kafka Data Management Machine Learning Operations Data Pipelines Databricks

Job description

We are seeking a Senior Data Engineer to design, build, and optimize scalable data solutions across Azure and GCP cloud environments. The ideal candidate will have strong expertise in Python, Vertex AI, feature engineering, and modern data engineering technologies., * Design, build, and maintain scalable data pipelines for ingestion, transformation, and integration using Kafka, Databricks, and related technologies.

  • Develop and manage feature engineering pipelines for machine learning workflows using Vertex AI, BigQuery ML, and Python.
  • Work with SQL, NoSQL, cloud-based, and real-time streaming data platforms.
  • Drive modernization and innovation across data platforms and engineering processes.
  • Develop automated unit, integration, and performance testing frameworks to ensure data quality and reliability.
  • Optimize data workflows for performance, scalability, and cost efficiency across large datasets.
  • Take ownership of systems and processes throughout the full SDLC, from design through deployment and support.
  • Collaborate with cross-functional teams to deliver internal and external-facing data solutions.
  • Create and review architecture diagrams, interface specifications, and technical documentation.

Requirements

  • Strong Python development experience.
  • Hands-on experience with Google Cloud Platform (GCP) and Azure.
  • Strong experience with Vertex AI and feature engineering.
  • Experience with Databricks, Kafka, and BigQuery/BigQuery ML.
  • Strong understanding of data pipelines, ETL/ELT, streaming, and distributed data processing.
  • Experience implementing automated testing for data applications and pipelines.
  • Strong SQL and experience working with large-scale datasets.
  • Excellent problem-solving, communication, and cross-functional collaboration skills.

About the company

About ManpowerGroup, Parent Company of: Manpower, Experis and Talent Solutions

Experis® is a global leader in technology services and part of the ManpowerGroup® (NYSE: MAN) family of brands. We connect skilled technology professionals with meaningful opportunities where they can grow their careers, expand their expertise and make a real impact. Guided by the belief that it takes Human Ingenuity to unlock the true potential of technology, Experis helps people gain experience with leading organizations, build sought-after skills and take the next step toward a brighter future. Backed by ManpowerGroup’s 75+ years of workforce expertise and global reach across more than 70 countries and territories, Experis brings the scale, insight and opportunity to help people and businesses thrive. ManpowerGroup is consistently recognized for its commitment to inclusion, ethics and responsible business, including being named one of the World’s Most Ethical Companies. Learn more at Experis.com.

ManpowerGroup is committed to providing equal employment opportunities in a professional, high quality work environment. It is the policy of ManpowerGroup and all of its subsidiaries to recruit, train, promote, transfer, pay and take all employment actions without regard to an employee’s race, color, national origin, ancestry, sex, sexual orientation, gender identity, genetic information, religion, age, disability, protected veteran status, or any other basis protected by applicable law.

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