Top Tech Jobs & Startup Jobs

Leads infrastructure automation, CI/CD architecture, Infrastructure as Code governance, Kubernetes platform reliability, incident response, and deployment security automation. The role also mentors DevOps engineers and supports cloud-native data solutions in SLA-driven environments. Preferred expertise includes multi-cloud automation, GitOps, DevSecOps, and deployment of Databricks or Snowflake data platforms.

Own quality assurance for an intelligent document extraction solution by authoring and executing functional, integration, regression, and end-to-end tests. Validate LLM extraction accuracy, structured JSON outputs, business rules, PII handling, compliance, and performance. Manage defects, coordinate with development and AI architecture teams, perform regression testing after model or schema changes, and support UAT with business stakeholders and operations teams.

Bridge business and technology for an AI-driven document extraction initiative. Document requirements, map current and target workflows, validate solution outputs, coordinate stakeholder sign-offs, define exception handling, and manage post-automation review processes. Facilitate Scrum ceremonies, maintain the product backlog, track sprint progress, remove impediments, escalate risks, and ensure agile delivery aligns with production timelines and compliance standards.

Designs and delivers enterprise Power BI dashboards and semantic models using Direct Lake and Azure Fabric Lakehouse data. Develops DAX measures, time-intelligence patterns, compliance and audit reporting, and domain-specific KPIs. Validates model and report accuracy, supports user acceptance testing, manages workspaces, publishes datasets, allocates access, and collaborates with Data Architects on governance and enterprise data model alignment.

Lead technical design and hands-on delivery of an AI-enabled SDLC platform. Build agent orchestration, memory, governance, audit, quality gates, and workflow automation across software development stages. Integrate Jira, Azure DevOps, GitHub, CI/CD, and AWS services while coding, debugging, testing, and deploying cloud-native applications. Lead stakeholder discussions, pilot execution, technical direction, and production validation with minimal oversight.

Lead infrastructure automation, CI/CD architecture, Terraform-based Infrastructure as Code governance, and Kubernetes platform reliability. Drive incident response, deployment security, compliance automation, and cloud-native data solution delivery. Mentor DevOps engineers and advance multi-cloud, GitOps, and DevSecOps practices across SLA-driven environments.

Provide L1/L2 production support for data platforms across cloud and on-premises environments. Monitor system performance and availability, troubleshoot incidents, conduct root cause analysis, analyze logs and metrics, support deployments, and implement fixes. Participate in major incident management, maintain operational documentation, meet SLAs and KPIs, and collaborate with Cloud, DevOps, and Engineering teams in a 24x7 rotational support model.

Operate and optimize cloud infrastructure, applications, and platform services across development and production environments. Responsibilities include reliability engineering, incident response, on-call support, infrastructure as code, CI/CD enablement, monitoring, security governance, disaster recovery, cost optimization, cloud migration support, and operational documentation. The role collaborates with DevOps, development, architecture, and security teams to automate deployments, improve performance, and maintain highly available cloud environments.

Analyze commercial real estate data to identify trends, validate data quality, and deliver actionable insights. Build optimized SQL queries, Power BI dashboards, DAX models, and governed datasets using Snowflake, PostgreSQL, and enterprise data platforms. Apply Python for transformation, automation, and advanced analytics, including AI/ML concepts. Partner with executives and stakeholders to gather requirements, present findings, and maintain documentation for data pipelines, models, and reports.

Leads the design, development, and deployment of scalable cloud-native data pipelines for enterprise analytics and reporting. Defines data engineering standards, reusable frameworks, governance, security, and compliance practices. Mentors engineers, conducts code and design reviews, makes architectural decisions, translates business needs into technical solutions, and owns end-to-end data initiatives in an Agile environment.