Improving
https://improving.comAbout
Improving is a leading IT professional services firm committed to helping companies achieve lasting success through modern technology. With core expertise in AI, Data, and Applications, we specialize in transforming legacy systems, building cloud-native platforms, and delivering intelligent, future-ready solutions for today’s complex business needs. Improving’s leaders are equally committed to fostering a great place to work that is inclusive and purpose-centered, empowering Improvers to bring their whole selves to work. Our team is known for its collaborative approach and long-term partnerships that prioritize measurable outcomes. By combining technical excellence with strategic insight, Improving enables all stakeholders to grow, adapt, and lead in an ever-evolving digital landscape.
Tech stack
Go Programming (Golang)
Java
Kubernetes
DockerCompany social profiles
Jobs at Improving
Summary -
- We are looking for a Cloud Infrastructure Engineer to build and operate the Azure foundation for our AI workloads and serve as the working bridge between the Cloud Infrastructure and Data teams. You will own Terraform-driven Azure infrastructure, DevOps pipelines, and hands-on platform components, including Azure AI Foundry, Model Context Protocol (MCP) servers, and Databricks.
Responsibilities -
- Build and maintain Azure infrastructure as code with Terraform, including reusable modules and multi-environment patterns.
- Provision and operate Azure AI Foundry hubs and projects, including model deployments, data connections, and identity and network configuration.
- Design and secure MCP servers that expose internal tools and data to AI agents.
- Partner with the Data team to deploy and configure Databricks workspaces, including VNet injection, private endpoints, Entra ID integration, and Unity Catalog.
- Own CI/CD pipelines in Azure DevOps or GitHub Actions for infrastructure and AI platform deployments.
- Enforce guardrails for AI workloads, including Key Vault secrets management, managed identities, and network isolation.
- Monitor platform health, reliability, and cost with Azure Monitor and Log Analytics.
- Triage cross-team platform requests, document reference patterns, and remove blockers between Cloud and Data teams.\
Requirements -
- 4 to 8 years of experience in cloud infrastructure or platform engineering.
- Strong hands-on Azure experience, including networking, Entra ID, RBAC, and managed identities.
- Advanced Terraform skills, including module design and state management.
- Working knowledge of DevOps practices, CI/CD, and Git-based workflows.
- Working knowledge of Azure AI Foundry or Azure OpenAI, including access control and network integration.
- Practical understanding of MCP and the security considerations for connecting AI agents to enterprise systems.
- Hands-on Databricks platform experience, including workspace deployment, Unity Catalog, and cluster configuration.
- Scripting skills in Python, PowerShell, or Bash.
- Experience working within SOC 2 Type II or similar control frameworks.
Preferred Qualifications -
- Experience with RAG architectures or Azure AI Search.
- Experience with GPU capacity and quota planning in Azure.
Lead Data Engineer – Databricks & Azure
- We are looking for a Lead Data Engineer with 5–7 years of experience in Azure, Databricks, and Microsoft Fabric to lead and mentor the data engineering team. The role involves implementing scalable data solutions using Databricks as the core platform, building modern data pipelines, and enabling seamless integration with Microsoft Fabric and Power BI.
Responsibilities & Requirements:
- Lead and mentor data engineers while driving hands-on technical delivery.
- Implement approved Databricks and Microsoft Fabric architectures and solutions.
- Develop metadata-driven bronze, silver, and gold data pipelines.
- Build reusable batch, incremental, CDC, and streaming ingestion pipelines.
- Strong hands-on experience with Azure Databricks, PySpark, SQL, and Delta Lake.
- Experience with Microsoft Fabric, OneLake, Direct Lake, and Power BI integration.
- Implement data quality checks, reconciliation, source-to-target mapping, and metadata management.
- Configure Unity Catalog for data governance, access control, auditing, and lineage.
- Implement CI/CD, automated deployments, and Datadog monitoring.
- Drive testing, documentation, operational readiness, and knowledge transfer.
Good to have:
- Experience with MDM and master data integration.
- Exposure to Azure DevOps or GitHub Actions.
- Experience with automated data testing and reconciliation frameworks.
- Experience working with onshore stakeholders and distributed engineering teams.
- Strong communication, problem-solving, and team leadership skills.
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