Mid-Level Data Engineer, Cloud Data Platforms

Kentro is a technology and mission-support company serving government customers through secure, innovative solutions. The Mid-Level Data Engineer will build governed cloud data pipelines, automate operational tasks, support Azure and Databricks platforms, and contribute to AI-enabled data workflows. The role also involves troubleshooting, infrastructure automation, documentation, and collaboration with technical and stakeholder teams.

Responsibilities:

• 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 intended audience

Requirements:

• Three to five years of relevant experience in data engineering, software engineering, cloud engineering, analytics engineering, or a closely related discipline
• Hands-on programming experience with Python or a comparable language, including reading unfamiliar code and debugging systematically
• Practical SQL experience with joins, aggregations, transformations, and row-level and aggregate validation
• Experience developing or supporting data pipelines, schemas, APIs, databases, cloud storage, or distributed data-processing workflows
• Working knowledge of Git, including commits, branches, pull requests, code review, and ordinary conflict resolution
• Experience testing work, retaining evidence, and writing documentation or runbooks that another engineer can follow
• Demonstrated ownership, learning agility, persistence, responsiveness, and follow-through when solving unfamiliar or ambiguous problems
• Ability to communicate technical status, risks, assumptions, and blockers clearly to both technical and nontechnical stakeholders
• Commitment to security, least privilege, responsible data handling, and compliance with customer requirements
• • US Citizen or Lawful Permanent Resident (Green Card)
• • Willing and able to obtain and maintain Public Trust Clearance or higher
• Experience with Azure, Azure Government, AWS, or another major cloud platform
• Experience with Databricks, Apache Spark, PySpark, Delta Lake, Lakeflow, or a comparable data-processing platform
• Experience with Terraform or another Infrastructure-as-Code tool
• Familiarity with Azure Data Lake Storage, Data Factory, Key Vault, Entra ID, managed identities, RBAC, private endpoints, DNS, or virtual networks
• Knowledge of data governance, catalogs, lineage, stewardship, audit trails, observability, and reproducible processing
• Experience with REST APIs, JSON/JSONL, CSV, Parquet, large-file processing, third-party ingestion, CI/CD, containers, or structured logging
• Exposure to AI/LLM-enabled applications, model-serving endpoints, evaluation, or automated regression testing
• Experience in a government, healthcare, or other regulated or compliance-sensitive environment
• Bachelor's degree in computer science, data science, information systems, engineering, or a related field, or equivalent relevant experience