Data Engineer/Scientist

CGI•Atlanta, GA

6d•Hybrid

About The Position

Bring your data engineering and data science experience to a top brand in Atlanta to build insights for stakeholders across the business. Build leading edge analytics models in the microbiology domain. If you are a person who is both technically adept and an excellent communicator who can take ownership of a mission critical data analysis platform, then this role is for you.

Requirements

Strong experience with data engineering pipelines and ELT processes.
Excellent ability to develop and publish data analysis reports that satisfy requests from the business
Ability to explain analytical findings and technical concepts to non technical stakeholders.
Proficiency in Python, SQL, Spark, and Databricks
Experience with AWS services such as S3, Glue, Lambda, Athena, and Step Functions.
Hands on knowledge of exploratory data analysis, statistical testing, feature engineering, machine learning models, and evaluation metrics.
Experience with Pandas, NumPy, scikit learn, and visualization libraries such as Matplotlib, Seaborn, or Plotly.
Knowledge of Delta Lake, data modeling, data quality, and performance optimization.
Strong problem solving, communication, and learning skills.

Nice To Haves

DataBricks 3, Very Good
Python, SQL, Spark, AWS, 3, Very Good
Data Engineering and ELT Pipelines, 3, Very Good
Data Analysis, 3, Very Good
Excellent Communication Skills, 3, Expert

Responsibilities

Build and maintain data pipelines using Databricks, Python, SQL, and Spark
Perform exploratory data analysis, hypothesis testing, feature engineering, and model evaluation.
Develop datasets and workflows that support machine learning models and analytical use cases.
Build clear visualizations (Tableau) and communicate findings through effective data storytelling.
Collaborate with stakeholders to translate business problems into data driven solutions.
Develop data pipelines using AWS services.
Monitor and improve production data and machine learning workflows.
Ensure data quality, reliability, security, and performance.