About Us:

Luxe Vision Consulting is a Wisconsin-based consulting firm dedicated to connecting top global talent with leading U.S. companies. We specialize in sourcing skilled professionals, conducting rigorous screening and technical assessments, and preparing candidates for opportunities in the U.S. job market.

Our mission is to bridge the gap between exceptional talent and top-tier businesses, ensuring the right fit for both candidates and clients. With a focus on quality, efficiency, and innovation, we help professionals unlock their potential and secure rewarding careers with prestigious U.S. organizations.

At Luxe Vision Consulting, we believe in integrity, excellence, and results-driven recruitment. Whether you're a company looking for the best talent or a professional seeking your next big opportunity, we are committed to making the connection that drives success.

The Role

Job Description:

We are looking for a skilled Data Engineer to join our team. The ideal candidate will have strong experience in designing, building, and maintaining scalable data pipelines and architectures. You will play a critical role in managing data workflows, ensuring data integrity, and optimizing data processing.

Responsibilities:

• Data Pipeline Development: Design, build, and maintain scalable and efficient data pipelines to process and transform large datasets.
• ETL & Data Integration: Develop and optimize ETL (Extract, Transform, Load) workflows for structured and unstructured data sources.
• Big Data Processing: Work with PySpark and Pandas to handle large-scale data processing tasks.
• Database Management: Design, implement, and manage relational (SQL) and non-relational databases for data storage and retrieval.
• Cloud Technologies: Leverage cloud platforms such as AWS, GCP, or Azure to deploy and manage data infrastructure.
• Collaboration: Work closely with data scientists, analysts, and software engineers to support analytical and machine learning projects.
• Data Quality & Performance Optimization: Ensure data accuracy, consistency, and security while optimizing performance.
• Monitoring & Troubleshooting: Identify and resolve data pipeline performance bottlenecks and failures.

Ideal Profile

Required Work Experience:

• 2+ years of experience in data engineering or a related field.
• Proven experience developing ETL pipelines and data processing workflows.
• Hands-on experience with PySpark, Pandas, and SQL.
• Experience working with big data technologies such as Apache Spark, Hadoop, or Kafka (preferred).
• Familiarity with cloud data solutions (AWS, GCP, or Azure).

Required Skills:

• Programming: Strong proficiency in Python (PySpark, Pandas) or Scala.
• Data Modeling & Storage: Experience with relational databases (PostgreSQL, MySQL, SQL Server) and NoSQL databases (MongoDB, Cassandra).
• Big Data & Distributed Computing: Knowledge of Apache Spark, Hadoop, or Kafka.
• ETL & Data Integration: Ability to develop efficient ETL processes and manage data pipelines.
• Cloud Computing: Experience with AWS (S3, Redshift, Glue), GCP (BigQuery), or Azure (Data Factory, Synapse).
• Data Warehousing: Understanding of data warehousing concepts and best practices.
• Problem-Solving: Strong analytical skills to troubleshoot and optimize data pipelines.
• Communication: Must be proficient in spoken English to collaborate with US-based teams.

Education Requirements:

• Bachelor’s degree in Computer Science, Data Engineering, Information Technology, or a related field (preferred).
• Equivalent work experience in data engineering will also be considered.
• 
  

Fill out the application form here: https://forms.gle/nefgwYRFYE7mffdA7

Alternatively, feel free to message us directly here on the page or email your resume to hiring@ luxevisionconsulting com

Subject: Position - First and Last Name

Only shortlisted candidates will be contacted. We look forward to hearing from you!

What's on Offer?

• Work within a company with a solid track record of success
• Attractive salary & benefits
• Excellent career development opportunities