Data Engineer

Overview

We are seeking a highly capable Data Engineer to join our team and support enterprise-level data initiatives. The ideal candidate demonstrates strong technical expertise, analytical problem-solving abilities, and the ability to collaborate effectively with both technical and non-technical stakeholders.

Position: Data Engineer

Location: Remote MN locals only - USC (Initially onsite for 2 months)

Type: Right-to-Hire

Get in touch with me at - NO FAKE or C2C PROFILES

Required Qualifications

• Bachelor's degree in Computer Science, Data Science, Social Science, Operations Research, Statistics, Applied Mathematics, Econometrics, or a related quantitative discipline. Equivalent experience and education in fields such as Economics, Engineering, or Physics will be considered.
• Minimum of 2 years of hands-on data engineering experience (a master's degree may substitute for experience).
• Minimum of 2 years' experience utilizing Python and/or R for data science programming.
• Minimum of 2 years working with SQL (including PL/SQL, PySpark SQL, or similar relational database programming languages).
• Practical experience with CI/CD pipelines and version control tools (Git preferred).
• Demonstrated understanding of data modeling techniques, including Star Schema, Snowflake Schema, denormalized modeling, and 3NF.
• Proficiency working with various data formats, such as Parquet, Avro, Delta, CSV, and JSON.
• Understanding of data processing methodologies, including batch processing, time-based partitioning, distributed processing, and real-time data operations.
• Strong data profiling and analytical skills with the ability to identify patterns and solve complex data problems.
• Self-motivated, curious, and capable of working independently.
• Effective communicator able to engage end users and collaborate with diverse development and operations teams.

Preferred Qualifications

Experience with Oracle ERP systems.

• Knowledge of healthcare operations and workflows.
• Understanding of basic accounting principles.
• Exposure to Agile/Scrum methodologies and collaborative project environments.
• Experience in a hybrid cloud environment with both on-prem and public cloud components.
• Hands-on experience with relational databases (Oracle, SQL Server).
• Expertise in SQL/Oracle performance tuning, including stored procedures and triggers.
• Experience with Python libraries such as NumPy, Pandas, Matplotlib, and Jupyter notebooks for EDA, machine learning, and automation.
• Exposure to CI/CD, continuous testing, and site reliability engineering practices.
• Familiarity with Microsoft Azure tools, including Azure Data Factory, Synapse, Purview, Databricks/Spark, Power BI, and PowerApps.
• Experience with NoSQL databases, particularly MongoDB.
• Ability to build robust Power BI data models using advanced Power Query and DAX.

How to Apply

If you meet the qualifications and are looking to join a dynamic team working with modern data platforms, we encourage you to apply.