Design and lead enterprise data architecture on the Databricks Lakehouse Platform, enabling analytics, AI, and operational reporting across a hybrid enterprise landscape.
Locations (2)
Newport News, Virginia, United States
United States
Compensation
$5,444.76 - $9,537.00
Responsibilities
Deliver strategic direction and leadership in enterprise-wide solution architecture
Execute design and improvements of architecture from design through completion
Guide definition of solution/system architecture across multiple products
Translate requirements into effective solution architecture
Participate in cross-architecture reviews and ensure integration
Requirements
Bachelor's degree in Computer Science, Information Technology, or a related field
Lead and grow a DevOps team, manage cloud environments, drive automation, and ensure secure, reliable operations for Sphera’s enterprise software products.
Responsibilities
Lead and grow your team
Balance workloads across product-line support, projects, and tickets
Own the hiring process: define role requirements, conduct interviews, and onboard new engineers
Develop talent by coaching engineers toward lead roles and leads toward management
Own your team’s backlog in Azure DevOps, turning requests into well-scoped epics, features, and backlog items
Design, develop, test, deploy, and maintain scalable data pipelines using Databricks and related technologies.
Responsibilities
Design, develop, test, deploy, optimize, and support complex, scalable, production-grade data pipelines using Databricks and related data engineering technologies.
Develop robust ETL/ELT solutions to ingest, transform, integrate, and deliver data across cloud and enterprise environments.
Design reusable and maintainable data integration patterns leveraging Databricks, Apache Spark/PySpark, Python, SQL, Delta Lake, APIs, and other appropriate technologies.
Design and maintain efficient data models, data structures, and storage solutions.
Implement data quality, validation, reconciliation, monitoring, and error-handling processes to ensure reliable and accurate data delivery.
Requirements
Bachelor's degree in computer science, Information Systems, Engineering, Data Engineering, or a related field, or equivalent professional experience
As a Technical Solution Architect, become a part of a cross-functional development team engineering experiences of tomorrow, focusing on AI transformation and replacing manual decision-making workflows with reliable, auditable AI-assisted systems.
Create and maintain scalable, reliable, and highly automated platforms for supporting development and operational activities using Azure.
Responsibilities
Design, implement, and maintain a shared platform that provides development teams with self-service capabilities for infrastructure provisioning, CI/CD, monitoring, and other common needs.
Manage infrastructure and deployments across Production and non-Production environments using scalable and automated processes.
Work closely with software development teams to understand their workflows, challenges, and goals, creating tools and processes that improve productivity and reduce friction in the developer lifecycle.
Drive the automation of infrastructure provisioning, configuration management, and application deployment pipelines using tools such as Azure DevOps, Infrastructure as Code, and scripting languages.
Integrate security and compliance requirements into platform solutions from the outset.
Design, build, test, deploy, and support scalable data pipelines and data products on Azure Databricks.
Compensation
Exempt roles are also performance bonus eligible
Responsibilities
Design, build, test, deploy, and support scalable data pipelines and data products on Azure Databricks.
Develop ingestion and transformation processes for data from on-premises, cloud, SaaS, and third-party sources using batch and, where appropriate, streaming patterns.
Use SQL and Python or PySpark to transform, validate, and optimize large and complex datasets.
Design and maintain reusable data structures across raw, refined, and curated layers, applying dimensional modeling and star schema principles where appropriate.
Build reliable Delta Lake solutions and apply Databricks capabilities for orchestration, performance, observability, and data quality.
Requirements
Bachelor’s degree in technology, engineering, computer science, or a related field, or an equivalent combination of education and experience.
Design and develop automation of infrastructure, championing best practices in service operation, delivery, scale, and observability.
Engage in the continuous integration and continuous deployment lifecycle of services, from design and inception through deployment, operation, and continuous refinement.
Contribute system design, capacity planning, and pre-production activities to support services before they go live.
Ensure optimal service performance by measuring and monitoring availability, latency, and system health. Implement sustainable scaling through automation and push for system evolution to boost reliability and deployment velocity.
Actively participate in incident response and conduct blameless postmortems to foster continuous improvement.
Requirements
Nice to have: build and deployment pipelines with Azure DevOps
Nice to have: Kubernetes
Nice to have: Azure
Nice to have: GCP
Nice to have: Security scans like Fortify, Veracode
Design, implement, and maintain core infrastructure that underpins the organisation’s applications and services, ensuring secure, scalable, and resilient systems.
Compensation
Competitive salary available, depending on experience
Responsibilities
Design and evolve cloud and on‑premises infrastructure with a focus on scalability, reliability, and performance, supporting migration of applications and databases from on-premise to Azure Cloud.
Implement identity, access control, and security best practices (Entra ID, RBAC, managed identities, Key Vault, secure baselines, patching).
Implement infrastructure‑as‑code (IaC) using tools such as Terraform, ARM/Bicep, or CloudFormation.
Collaborate with DevOps, Networking, Security, and Engineering teams to deliver integrated, compliant and robust Azure Cloud platform solutions and maintain clear documentation.
Manage patching, vulnerability remediation, and secure configuration baselines.
The Software Engineer is responsible for coding, testing and implementing products for our HRS Platform Team, which is increasingly focused on agentic and AI-driven engineering.
Responsibilities
Design, build, test and ship full-stack features in C#/.NET, ASP.NET Core Web APIs, SQL and a modern web front end.
Write code that meets design specifications, follows team standards, and is easy to maintain.
Review functional and technical requirements, research options, and propose designs.
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