Mid-Level Data Engineer, Cloud Data Platforms

Thank you for considering IT Concepts dba Kentro, where innovation drives opportunity and collaboration leads to success. Our dynamic community of experts is fully committed to advancing our customers' missions, fostering professional growth, and making a positive impact on our communities.

By joining our supportive community, you will find that Kentro is dedicated to your personal and professional development. Together, we can drive meaningful change, spark innovation, and achieve extraordinary milestones.

Kentro is hiring for a Mid-Level Data Engineer to support secure cloud data and applied AI initiatives for government customers. You will build governed data pipelines, automate cloud and operational tasks, solve cross-layer technical problems, and turn evolving requirements into reliable, well-documented solutions. This role is well suited to an engineer who brings strong fundamentals and, above all, the drive to take ownership, learn quickly, communicate clearly, and see important work through to a verified outcome.

You will contribute independently within a defined scope while collaborating with technical leaders and growing toward broader platform ownership.

Location: Remote - This position can be performed remotely within the United States and will support Eastern Time working hours.

Compensation Range: The pay range for this position is $,000K annually. Kentro determines compensation by evaluating current government contracting and commercial market conditions, as well as the role’s specific requirements. Final salary placement within this range will be based on the candidate’s relevant skills, experience, education, certifications, location, and security clearance level, where applicable.

This Job Description reflects the primary duties of the role; however, it is not intended to be all‑inclusive. Team members may be asked to take on additional responsibilities in alignment with customer expectations, business needs, and Kentro’s culture of collaboration and adaptability.

• Develop, test, deploy, and maintain batch and API-based data ingestion, transformation, and publishing workflows.
• Write clear, maintainable Python, PySpark, and SQL for data processing, validation, reconciliation, and automation.
• Build and support Databricks workflows using notebooks, jobs, compute, Delta tables, catalogs, schemas, permissions, and governed data products.
• Implement layered data designs, including landing/raw, Bronze, Silver, and curated or presentation outputs.
• Add data-quality checks, lineage, audit metadata, checksums, retry and recovery behavior, logging, and reproducible tests to pipelines.
• Support Azure data-platform services, cloud storage, secrets, workload identities, role-based access, monitoring, networking, and private connectivity.
• Develop and review Infrastructure as Code, primarily Terraform, using reusable modules and environment-specific configuration.
• Deliver traceable changes through Git branches, pull requests, code reviews, issue tracking, and CI/CD workflows.
• Troubleshoot data, code, access, authentication, permissions, deployment, networking, and runtime issues using logs, tests, queries, and documented evidence.
• Support AI-enabled data workflows, including model endpoints, response validation, evaluation, regression testing, and responsible-use controls.
• Create and maintain architecture diagrams, runbooks, implementation notes, decision records, status updates, and handoff documentation.
• Communicate progress, risks, availability, and blockers promptly; ask for help early enough to protect delivery and close the loop on commitments.
• Participate in stand‑ups, design reviews, demonstrations, and stakeholder discussions, translating technical findings for the…