Vital Tech Solutions

Data Engineer

• Design, build, and maintain batch and streaming data pipelines using PySpark, SQL, Databricks Workflows, and Delta Live Tables
• Implement Medallion Architecture across bronze, silver, and gold data layers
• Develop scalable ingestion frameworks for structured, semi-structured, and unstructured data
• Integrate data from files, databases, APIs, Kafka, Kinesis, and Databricks Auto Loader
• Design dimensional and domain-specific data models
• Build and consume APIs for downstream system integration
• Optimize Spark workloads for performance and cost through partitioning, caching, cluster sizing, and related techniques
• Develop data quality checks, validation processes, and pipeline monitoring
• Maintain documentation covering data flows, lineage, architecture, and integration points
• Collaborate with engineering, platform, architecture, and federal program stakeholders throughout the development lifecycle

Data Engineer, Databricks

DevOps Engineer

• Maintain, monitor, and troubleshoot production environments to support system uptime, reliability, and performance
• Manage and operate infrastructure using Terraform, Ansible, and Docker
• Support and maintain CI/CD pipelines and automate operational workflows using Git and related tooling
• Ensure the ongoing reliability of systems operating within AWS environments, including EKS, S3, and EMR
• Support operational use of Spark, JupyterHub, and Hue
• Diagnose and resolve infrastructure and application issues
• Conduct root-cause analysis and drive long-term resolution of recurring incidents
• Implement, refine, and maintain infrastructure and application monitoring, alerting, and diagnostics
• Support deployment activities, maintenance windows, and production changes
• Optimize data flows and storage integrations
• Collaborate with engineering, product, and client stakeholders to communicate issues, coordinate maintenance, and support operational priorities
• Contribute to continuous improvement of operational processes, platform documentation, and reliability best practices

Senior Site Reliability Engineer, SRE

Platform Engineer

• Design, deploy, govern, and support enterprise Databricks environments for a federal client
• Deploy and configure Databricks workspaces from the ground up using Terraform and Databricks Secure Reference Architecture across development, test, and production environments
• Support Databricks deployments within AWS Commercial and AWS GovCloud environments
• Design and implement AWS networking architecture, including VPCs, subnets, PrivateLink, Transit Gateway, security groups, and DNS
• Manage Databricks control-plane and data-plane connectivity
• Administer Unity Catalog, including metastores, catalogs, schemas, external locations, permissions, grants, and row- and column-level security
• Build and maintain CI/CD pipelines supporting infrastructure deployment and Databricks Asset Bundles
• Establish platform governance standards, architectural guardrails, tagging strategies, naming conventions, and operating best practices
• Automate provisioning and administration of cluster policies, secrets, service principals, SSO, and SCIM integrations
• Monitor platform health, utilization, performance, and cost
• Identify opportunities for rightsizing, cost optimization, and improved platform efficiency
• Serve as an escalation point for platform incidents, troubleshooting, and root-cause analysis
• Partner with technical and business stakeholders on platform architecture, governance, security, and operational decisions

Data Engineer, Databricks

Senior Site Reliability Engineer, SRE

Databricks Platform Engineer