Mid-Level Data Engineer

Chenega Corporation • Springfield, VA

16h • Hybrid

About The Position

The Data Engineer is responsible for designing, developing, and maintaining enterprise data pipelines, dashboards, and visualization solutions that support operational monitoring, analytics, and decision-making. This role works with enterprise monitoring platforms, cloud technologies, databases, APIs, and automation tools to collect, transform, and visualize operational data while ensuring data quality, reliability, and scalability. The ideal candidate has strong experience with Python, SQL, cloud-based data engineering, ETL/ELT processes, and data visualization, along with the ability to communicate technical findings to both technical and non-technical stakeholders.

Requirements

• High School Diploma or GED equivalent with 8+ years of relevant experience OR: Associate’s degree and 6+ years’ experience OR: Bachelor’s Degree and 4+ years’ experience
• Experience designing and maintaining ETL/ELT pipelines.
• TS/SCI clearance
• Successfully pass background and drug screening
• Strong knowledge of cloud environments (AWS, Azure, or GCP).
• Familiarity with data warehousing, data modeling, and version control systems (e.g., Git).
• Excellent analytical, organizational, and communication skills.
• Proficiency in Python, SQL, and working with RESTful APIs.
• Ability to work independently and yet be effective within a team setting
• Must be capable of managing multiple efforts with time-related constraints in a fast-paced contracting environment
• Demonstrated ability to effectively communicate and collaborate with diverse internal and external stakeholder groups and individuals
• Friendly presence, helpful attitude, good interpersonal skills, and ability to work well with others.
• Excellent skills in Microsoft Word, Excel, and other Office applications
• Proficient with Microsoft Office Applications, and experience working in a home office setting as well as the ability to train end users on frequently asked technical issues.
• Ability to provide technical assistance and support over the phone; good phone skills, professional demeanor, and previous customer service experience strongly desired.
• Good problem-solving skills; ability to visualize a problem/situation and think abstractly to solve it

Nice To Haves

• Experience designing and developing dashboards, reports, and data visualizations using tools such as Grafana, Power BI, Tableau, Kibana, or similar platforms.
• Experience automating data workflows using Apache Airflow or similar orchestration tools.
• Experience with cloud platforms and services such as AWS (S3, Lambda, Glue), Azure Data Factory, or Google BigQuery for data storage, processing, and orchestration.
• Familiarity with secure, scalable, and cost-effective cloud data solutions.
• Familiarity with CI/CD practices in data engineering environments.

Responsibilities

• Work with enterprise monitoring tools including Grafana, Prometheus, and ServiceNow to integrate operational events, service impacts, and system metrics into dashboards and visualizations.
• Quickly learn and apply new enterprise monitoring, visualization, analytics, and data platforms as business needs evolve.
• Design, build, and maintain interactive dashboards, reports, charts, and visualizations that communicate operational performance and actionable insights.
• Translate monitoring and analysis results into meaningful operational metrics that support decision-making.
• Collect, clean, transform, and organize data from SQL/NoSQL databases, APIs, streaming services, and flat files to ensure accuracy, consistency, and reliability.
• Build, maintain, and optimize ETL/ELT pipelines and data ingestion workflows for centralized data repositories and reporting.
• Implement data validation and quality checks to maintain data integrity across data platforms.
• Develop scripts and automation to streamline repetitive tasks and improve operational efficiency.
• Investigate and troubleshoot data pipeline, observability, monitoring, and reporting issues independently and collaboratively.
• Collaborate with stakeholders, managers, analysts, and technical teams to translate business requirements into scalable data solutions.
• Maintain documentation for data systems, workflows, and business rules.
• Utilize Git for version control and follow established development best practices to support reliable deployment and maintenance of data solutions.
• Present technical findings to both technical and non-technical audiences.
• Collaborate with team members and share knowledge of tools, processes, and best practices.
• Analyze large datasets to identify trends, anomalies, and opportunities for operational improvement.
• Apply data modeling and data storytelling techniques to transform raw data into actionable insights.
• Perform other duties as assigned.
• Other duties as assigned

Benefits

• professional development is embedded in your employer’s core culture
• opportunities to help sharpen skills in addition to hands-on experience in the global, fast-changing business world
• on-the-job learning experiences
• formal development programs
• well-being programs

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level