Data Engineer and Modeler

CGI•Durham, NC

4d•Onsite

About The Position

We are seeking an experienced Data Engineer and Modeler with deep expertise in designing relational data models, building scalable ETL/ELT pipelines, and processing large datasets across modern cloud environments. This role is ideal for engineers who excel at transforming complex data into reliable, high quality structures that power enterprise applications, analytics, and reporting. You will work closely with engineering, analytics, and product teams to deliver robust, cloud native data solutions on AWS. This position is located on site in Durham, NC.

Requirements

6-9 years of software development experience, with a strong focus on data engineering.
Extensive experience handling and processing large volumes of data.
Strong proficiency in RDBMS data modeling for operational and reporting systems.
Hands on experience with Oracle, Postgres (Aurora RDS), and Snowflake.
Proficiency in Python for large scale data analysis, transformation, and automation.
Strong experience with Java, including building APIs and microservices.
CI/CD and containerization experience with Jenkins, UDeploy, Docker, and Kubernetes.
Solid understanding of ETL/ELT tools and processes.
Experience with data migrations, including mapping, validation, and reconciliation.
Hands on experience with AWS cloud computing and cloud native development.
Strong communication, organizational skills, and attention to detail.

Nice To Haves

Experience with distributed data processing frameworks (e.g., Spark, Flink).
Familiarity with data warehousing concepts and dimensional modeling.
Experience with event driven architectures or streaming data pipelines.
Ability to collaborate effectively with analytics, BI, and product teams.
Strong problem solving skills and ability to work in fast paced environments.

Responsibilities

Design, develop, and optimize data pipelines to process large volumes of structured and unstructured data.
Build and maintain relational data models (RDBMS) for transactional systems, operational data stores, and reporting environments.
Work extensively with Oracle, Postgres (Aurora RDS), and Snowflake databases.
Perform large scale data analysis, transformation, and automation using Python, including handling massive datasets.
Develop and maintain Java based APIs and microservices for data access, ingestion, and integration.
Implement CI/CD workflows using Jenkins, UDeploy, and container technologies such as Docker and Kubernetes.
Design and support ETL/ELT processes, ensuring data quality, reliability, and performance across pipelines.
Lead and execute data migration initiatives, including schema mapping, validation, reconciliation, and cutover planning.
Build cloud native data solutions using AWS services such as RDS, S3, Lambda, Glue, and more.
Collaborate with cross functional teams to understand data requirements and deliver scalable, high performing solutions.
Maintain strong documentation, data governance practices, and adherence to engineering best standards.