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Job Summary: The Data Engineer will design, construct, install, and maintain large-scale processing systems that collect, manage, and convert raw data into usable information for data scientists and business analysts. Their primary goal is to make data accessible and optimized for performance to drive decision-making within the organization. The ideal candidate should be able to build and maintain efficient data pipelines and ensure seamless data integration from various sources.

Key Responsibilities:

• Develop, construct, test, and maintain data architectures (databases, large-scale processing systems, and data lakes).

• Assemble and optimize data pipelines to gather and process raw data at scale for use in analytics and machine learning models.

• Work closely with data scientists and analysts to ensure the accuracy and relevance of the data for analysis.

• Design and implement data storage solutions, ensuring high data quality and accessibility.

• Manage the integration of structured and unstructured data from various sources into the organization's data systems.

• Optimize data systems and pipelines for improved performance and scalability.

• Implement data governance and ensure adherence to data privacy and security protocols.

• Collaborate with software engineers and architects to ensure seamless data flow between systems.

• Troubleshoot and resolve data-related issues and provide support to stakeholders on data usage.

Basic Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field.

• 3+ years of experience as a data engineer or in a similar role.

• Proficiency in programming languages such as Python, Java, or Scala.

• Hands-on experience with databases (SQL, NoSQL), data warehousing, and ETL (Extract, Transform, Load) processes.

• Familiarity with big data tools such as Hadoop, Spark, or Kafka.

• Experience with cloud platforms like AWS, Azure, or Google Cloud for data storage and processing.

• Strong knowledge of data modeling, data integration, and data visualization tools.

• Excellent problem-solving and analytical skills.

• Strong communication and collaboration skills.

Preferred Qualifications:

• Experience with building data pipelines, data pipeline infrastructure and related tools and environments used in analytics and data science (ex: Python, Unix)

• Experience in developing analytic workloads with AWS Services, S3, Simple Queue Service (SQS), Simple Notification Service (SNS), Lambda, EC2, ECR and Secrets Manager.

• Strong proficiency in Python, SQL, Linux/Unix shell scripting, GitHub Actions or Docker, Terraform or CloudFormation, and Snowflake.

• Experience automating data ingestion, processing, and reporting/monitoring.

• Experience with orchestration tools such as Prefect, DBT, or Airflow.

• Experience with other relevant tools used in data engineering (e.g., SQL, GIT, etc.)

• Ability to set up environments (Dev, QA, and Prod) using GitHub repo and GitHub rules/methodologies; how to maintain (via SQL coding and proper versioning)

What's in it for you?

• Hybrid or remote work environment

• Weekly W2 payroll

• 401K + Benefits

• Tenured paid holidays

• Work for our Fortune 500 companies or start-ups!

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.