Data Activation Engineer I

CONA Services•Charlotte, NC

1d•Onsite

About The Position

The IT Data Activation Engineer I is an early-career developer responsible for assisting in the design, development, and maintenance of software applications under the guidance of senior team members. This role typically involves writing clean, efficient code, debugging programs, and collaborating with colleagues to solve technical challenges. Junior developers are expected to participate in code reviews, learn new technologies, and follow best practices in software development. Junior developers are encouraged to explore and adopt artificial intelligence tools and frameworks, and to integrate AI concepts into their work where appropriate.

Requirements

1–3 years of experience (internship, co-op, or full-time) in data engineering, analytics engineering, or data warehousing
Basic to intermediate SQL skills and understanding of relational data concepts.
Exposure to Snowflake and/or cloud data platforms (through coursework, projects, or professional experience).
Familiarity with dbt concepts (models, sources, tests, documentation) and willingness to learn team patterns.
Basic Python experience for scripting and data tasks (e.g., simple automation, file handling, data manipulation).
Exposure to Azure fundamentals (storage concepts such as ADLS, basic ADF awareness) is a plus.
Experience with Git basics (branching, pull requests) or willingness to learn.
Two years of education beyond high school in college or technical school
One to up to three years of relevant work experience

Nice To Haves

Bachelor's degree, particularly in Information Systems, Computer Science, Engineering
Certifications in Data Engineering, Snowflake, DBT preferred.

Responsibilities

Develop and maintain SQL queries, views, and transformations in Snowflake under team guidance.
Create and update dbt models, tests, and documentation following established project standards.
Assist with data ingestion and pipeline support on Azure (e.g., Azure Data Factory, SSIS), including file loads and troubleshooting.
Perform data validation and reconciliation checks to support data quality and resolve issues.
Support performance and cost best practices by following query standards and raising optimization opportunities.
Partner with analysts/BI developers to understand dataset needs and support reporting, while learning and applying dimensional data modeling fundamentals (facts, dimensions, and SCD patterns) with guidance.
Engage in continuous self-improvement by completing training, certifications, and learning opportunities to expand technical skills and domain knowledge.
Participate in on-call support rotations, routine maintenance activities, and other duties as determined by the team.
Other duties as assigned.