Job Listings

- Proven experience as a Cloud Architect, Data Engineer, or System Engineer in enterprise environments.
- Strong understanding of cloud architecture, networking, and security best practices.
- Hands-on experience delivering custom solutions on a major public cloud platform (GCP preferred).
- Ability to manage multiple projects simultaneously with strong organizational skills.

Experience & Track Record

• 5+ years of project management experience with at least 2 years focused on cloud technology projects
• Demonstrated success managing complex projects on-time and on budget with teams of 5–10+ members
• Proven ability to manage multiple concurrent projects with varying complexity and stakeholder needs
• Experience with Agile/Scrum methodologies and iterative delivery approaches
• Strong track record of building client relationships and achieving 85%+ satisfaction scores

Google Cloud Platform Expertise

• Google Cloud Associate Cloud Engineer certification is preferred (or Professional Cloud Architect/Developer/DevOps Engineer)
• If not currently certified: commitment to achieve Associate Cloud Engineer within 3 months and Professional Cloud Architect within 12 months of hire
• Hands-on familiarity with core GCP services: Compute Engine, GKE, Cloud Run, BigQuery, Cloud Storage, Cloud SQL, Pub/Sub, and Cloud Functions
• Understanding of cloud migration methodologies (lift-and-shift, re-platform, re-architect) and infrastructure modernization patterns

Technical Foundation

• Solid understanding of cloud architecture concepts including networking, security, identity management, and infrastructure-as-code
• Familiarity with DevOps practices, CI/CD pipelines, and containerization (Docker, Kubernetes)
• Ability to engage in technical discussions with architects and engineers while understanding business implications
• Proficiency with Atlassian tools: Jira (project tracking, workflows, dashboards), Jira Service Management (request handling, SLA tracking), and Tempo (time tracking, resource planning, financial reporting)

Core Competencies

• Exceptional communication skills with ability to translate complex technical concepts for executive audiences
• Strong organizational and time management capabilities with attention to detail
• Proactive problem-solving approach with ability to navigate ambiguity and competing priorities
• Collaborative leadership style that builds trust across technical teams and business stakeholders
• Bachelor's degree in Computer Science, Information Systems, Business, Engineering, or related field (or equivalent practical experience)

- Experience selling PaaS/SaaS solutions
- Demonstrated success selling B2B software
- Ability to source, engage, and build relationships with target accounts
- Excellent written and verbal communication abilities
- Skilled in leading video-based presentations and meetings
- Capable of working with sales engineers and customer technical leads to inventory software environments, define migration strategies, and build business cases
- Strong interpersonal and collaboration abilities

- Experience: 3+ years of experience in a customer-facing technical role, such as sales engineering, solutions architecture, or consulting.
- Cloud Proficiency: Deep understanding of cloud computing concepts and technologies, with hands-on experience with Google Cloud Platform (GCP).
- Technical Skills: Proficiency in cloud-native technologies like Kubernetes, containers, and serverless computing. Experience with infrastructure-as-code, automation tools, and scripting languages.
- Communication Skills: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
- Presentation Skills: Proficient in leading technical presentations and product demonstrations.
- Problem-Solving: Strong analytical and problem-solving skills, with the ability to troubleshoot technical issues and identify solutions.
- Collaboration: Ability to work effectively in a team environment, collaborating with colleagues and customers.

Experience & Track Record

• 4+ years of experience in designing and deploying AI/ML or data-driven solutions, preferably within cloud environments.
• Hands-on experience with Google Cloud AI/ML services (Vertex AI, AutoML, BigQuery ML).
• Strong background in data processing, machine learning lifecycle management, and model operationalization.
• Experience developing proof-of-concepts or production-grade AI applications using Python and frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Demonstrated ability to work collaboratively with technical and business teams in client-facing roles.

Google Cloud Platform Expertise

• Google Cloud Professional Machine Learning Engineer or Professional Data Engineer certification preferred.
• If not currently certified, commitment to achieve Associate Cloud Engineer within 3 months and Professional Machine Learning Engineer within 12 months of hire.
• Strong familiarity with key GCP services: BigQuery, Vertex AI, Dataflow, Cloud Run, Cloud Functions, and Cloud Storage.
• Understanding of MLOps best practices, model monitoring, and continuous training workflows.

Technical Foundation

• Proficiency in Python and SQL; familiarity with notebooks such as Vertex AI Workbench or Jupyter.
• Experience with data pipeline orchestration using Composer, Dataflow, or Airflow.
• Knowledge of API design, microservices, and containerization using Docker and Kubernetes (GKE).
• Understanding of responsible AI principles, data governance, and security best practices in cloud environments.

Core Competencies

• Excellent communication skills and ability to translate technical AI concepts into business value.
• Strong analytical and problem-solving mindset with attention to detail.
• Curiosity-driven and proactive in identifying opportunities for automation and optimization.
• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field (or equivalent practical experience).

- GCP Expertise: Proven experience in designing, building, and deploying data solutions on GCP.
- Data Warehousing and Pipelines: Strong expertise in SQL, data warehouse design, and data pipeline development.
- Cloud Architecture: Understanding of cloud architecture principles and best practices.
- Communication Skills: Excellent written and verbal communication skills, including the ability to explain technical concepts to non-technical stakeholders.

Experience & Track Record

• 4+ years in BI, data analytics, or data engineering, including 2+ years with Looker.
• Expertise creating and maintaining LookML models, Explores, and dashboards.
• Ability to translate business requirements into technical analytics solutions.
• Experience integrating Looker with BigQuery and Google Cloud data services.
• Strong analytical, visualization, and communication skills.

Google Cloud Platform Expertise

• Experience with BigQuery, Dataform, Cloud Storage, and Cloud SQL.
• Understanding of data modeling, ELT pipelines, and SQL optimization in GCP.
• Looker Business Analyst or Data Analyst certification preferred.
• If not certified, commitment to obtaining Looker Business Analyst certification within 6 months.

Technical Foundation

• Proficiency in SQL and LookML development.
• Familiarity with Dataform, dbt, or Cloud Data Fusion.
• Understanding of data governance, access management, and metadata design.
• Ability to integrate Looker with BigQuery ML and Vertex AI.
• Experience with Git, Agile workflows, and CI/CD for LookML.

Core Competencies

• Strong communication skills bridging technical and business needs.
• Excellent organizational skills and attention to detail.
• Passion for scalable data-driven analytics solutions.
• Bachelor’s degree in a relevant field or equivalent experience.