• Operating within a process-driven, enterprise environment, ensuring strict adherence to established operational and change management procedures. • Designing, implementing, and supporting Data Center networking solutions using Cisco and Arista technologies. • Managing and optimizing routing protocols, with a strong focus on BGP in complex enterprise environments. • Designing, implementing, and supporting Cloud Networking solutions across AWS (preferred), Azure, or GCP environments. • Collaborating with global stakeholders and technical teams, providing professional communication and support in English. • Working closely with a broader DC/Cloud Networking team while maintaining the ability to deliver tasks independently. • Supporting operational activities, including scheduled Saturday work (typically two Saturdays per month, depending on workload). • Maintaining high attention to detail across configuration, documentation, implementation, and troubleshooting activities. • Contributing to automation initiatives using Python scripting where applicable. • Ensuring stable operations across hybrid environments, including basic interaction with Windows and Linux systems.

Role Description The Inviso Lead Cloud Architect is a senior technical leader who designs, scopes, and delivers modern Data & AI solutions on Microsoft Azure. This role owns client engagements end-to-end, partnering with executive and technical stakeholders to translate business objectives into scalable, governed, production-ready architectures. - The Architect leads technical presales and delivery. - Provides architectural direction to delivery teams. - Ensures high standards of quality, customer satisfaction, and business impact. - Collaborates closely with Practice Leadership and peer architects to evolve cloud offerings. - Supports the continued growth of Azure consulting services. This is a 100% remote role, where employees are in the USA, working US business hours. Qualifications - 8+ years of experience designing, architecting, and delivering Microsoft data and analytics solutions. - Proven experience leading end-to-end implementations of Azure, Microsoft Fabric, or Databricks data platforms. - Strong expertise in PySpark, SQL, Python, ETL/ELT, and software/data engineering patterns. - Experience building scalable lakehouse architectures and medallion data models. - Experience with CI/CD deployment automation using Azure DevOps and GitHub. - Strong knowledge of Azure services including Azure Data Factory, Azure SQL, Azure Storage, Azure Data Lake Storage, and related services. - Experience with performance optimization, cost management, and production-grade governance. - Experience leading project teams and evaluating technical deliverables. - Strong verbal and written English skills. - Experience participating in technical sales cycles, proposal development, or client scoping. - Knowledge of Data Vault or dimensional modeling methodologies preferred. Requirements - Microsoft Cloud certifications (Fabric, Azure Data Engineer, or Azure Architect). - Bachelor’s degree (or higher) in a related field. - Experience with AI/ML frameworks and production AI workloads. - Experience supporting enterprise-scale data modernization initiatives. Success Criteria Architect success is measured through delivery excellence, achievement of personal and team revenue/utilization targets, and high customer satisfaction scores. This role is accountable for both individual performance and the performance of assigned delivery teams, ensuring projects are delivered on time, on budget, and aligned to client business objectives. Compensation Our compensation reflects the cost of labor across several US geographic markets. The pay for this position is between $150,000 up to $200,000 OTE (Base + bonus) annually. The range displayed on this job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is based on several factors including market location, job-related skills, experience, and relevant education or training, as well as Inviso’s differing lines of business. In addition to the base pay, Inviso provides access to medical, dental, and vision insurance, a 401(k) plan and company match, annual training reimbursement, paid time off, and paid holidays, among other benefits. Why Inviso? Our Culture & Values are who we are. Our commitment to excellence is interwoven with the way we care about our people. Our low attrition rate, high average employee tenure, and the number of people that have been with Inviso for 10, 15, even 20 years, speaks volumes to who we are as a company. - We are a meritocracy through and through. Those who excel, grow. There is no ceiling, we don’t tolerate politics. - Inviso has maintained a deep, well-established relationship with Microsoft for over 20 years. - We are a top-rated supplier and are proud to be a Managed Partner with many credentials.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are seeking a skilled Mid-Level Data Engineer to join our Data Platform team. At this level, you will be a hands-on executor and domain owner — responsible for building, maintaining, and improving the pipelines and data models that power analytics and business intelligence across the company. You will own specific areas of our BigQuery data warehouse end-to-end, delivering reliable data products within a framework set by senior and staff engineers. This is not an architecture or strategy role — it is a role for someone who takes well-defined problems and executes them with high craft and reliability. You will work closely with data analysts, analytics engineers, and product teams, and are expected to grow toward greater technical ownership over time. - Build and maintain production-grade ELT pipelines that ingest data from internal applications, third-party SaaS tools, and event streams into our BigQuery data warehouse. - Own specific data domains end-to-end — from raw ingestion through to marts — ensuring your areas of the warehouse are accurate, tested, and well-documented. - Write and maintain dbt models, tests, macros, and documentation within our established dbt project conventions and code review process. - Develop and manage Airflow DAGs on Cloud Composer or other similar tools to orchestrate data workflows, following patterns and standards set by the team. - Implement data quality checks and monitoring to catch anomalies before they reach downstream consumers. - Optimize BigQuery queries and models for cost and performance within your domain, escalating architectural tradeoffs to senior engineers when appropriate. - Collaborate with analysts and stakeholders to translate business data needs into well-scoped pipeline and modeling tasks. - Participate in on-call rotations, respond to pipeline incidents, and write clear postmortems. - Contribute to team documentation and runbooks so that your work is maintainable by others. Qualifications - 3–5 years of experience in data engineering or a closely related data infrastructure role. - Proven experience designing and implementing scalable data pipelines and warehouse architectures. - Strong expertise in Google Cloud Platform (BigQuery, Cloud Storage, Cloud Composer, Pub/Sub, Dataflow). - Hands-on experience with dbt (data build tool) — models, tests, macros, sources, and documentation — at production scale. - Experience building and maintaining data pipelines with Apache Airflow or a comparable workflow orchestration tool. - Strong proficiency in SQL, including advanced BigQuery SQL (window functions, partitioning, clustering, query optimization). - Proficiency in Python for data engineering tasks, including API integrations, data processing scripts, and custom operators. - Familiarity with data modeling concepts: star schema, dimensional modeling, slowly changing dimensions (SCD). - Experience with version control (Git) and collaborative development workflows (pull requests, code review). - Understanding of data quality, lineage, and observability best practices. - Startup or growth-stage mindset — comfortable with ambiguity, rapid iteration, and evolving priorities. - Excellent communication skills, with the ability to collaborate effectively across technical and non-technical teams. Requirements - Experience with Terraform or similar infrastructure-as-code tools for managing cloud data infrastructure. - Familiarity with streaming technologies such as GCP Pub/Sub, Dataflow, or Apache Kafka. - Knowledge of Looker, Tableau, or other BI tools and how data models power them. - Google Cloud Professional Data Engineer certification. Benefits - Work on a modern, best-in-class GCP and BigQuery data stack with a high-performing team. - Influence data platform architecture decisions and grow into a senior or staff engineering role. - Competitive compensation, equity, and benefits with a culture that values engineering craft and continuous learning. - Annual salary + bonus. - A remote first culture! - Flex PTO. - Health, Dental and Vision Insurance. - 13 Paid Holidays. - Company volunteer days.

• Provide meaningful input to technical designs and direct hands-on contributions to projects in the cloud networking space • Grow, lead, and manage a small team of talented engineers • Support your team's professional growth and maintain high performance through mentorship and coaching • Work with tech leads, peers, and partners to define and execute on a coherent vision and roadmap for Airbnb’s cloud network infrastructure and related components • Work with open source communities (e.g. istio) to build the next generation service mesh for all Airbnb back-end services • Build cross-region gateways and load balancers for global Airbnb services • Work with external partners and internal engineering and security teams to deliver edge security systems that protect Airbnb services • Nurture a culture of technical quality from design, through code review, to production • Build strong partnership and alignment with teams across engineering