Solutions Architect/Sr. Solutions Architect
Listed on 2026-09-02
-
IT/Tech
Data Engineering, Cloud Computing: Infrastructure & Operations, Data Warehousing
Location: Atlanta
Data Architect
What you need to succeed
• 8+ years in data architecture or data engineering with strong, recent hands on experience on Google Cloud as a must have.
• Proven presales experience with clients, including workshops, solution scoping, estimates and proposal content.
• Deep skills in Google Cloud data services (Big Query, Dataflow, Dataproc, Pub/Sub, AlloyDB, Cloud Composer, Looker) and practical Snowflake expertise (roles, warehouses, performance and cost tuning).
• Hands on work with ML or GenAI (Vertex AI or similar), strong SQL and Python and familiarity with LLM, vector and agentic patterns.
• Knowledge of AWS data services (S3, Glue, Redshift, Lambda) and experience with data governance, security and Responsible AI in enterprise environments.
Education and certifications
• Bachelor's degree in computer science, information technology, engineering or a related field, or equivalent practical experience commonly expected for cloud and data architects.
• Certifications such as Google Cloud Professional Cloud Architect, Google Cloud Professional Data Engineer, Snowflake Snow Pro Advanced Architect or AWS Solutions Architect Professional are strongly preferred.
Nice to have
• Experience with BI tools such as Power BI, Tableau, Looker or Looker Studio for analytics and dashboarding.
• Experience with infrastructure as code and Dev Ops for data, for example Terraform, Cloud Deployment Manager, Git based workflows and CI/CD for pipelines.
• Consulting background and contributions to data or AI communities through blogs, talks or meetups.
What you will do
• Architect end to end data and AI platforms using Google Cloud (Big Query, Dataflow, Dataproc, Pub/Sub, AlloyDB, Vertex AI, Cloud Composer) and Snowflake.
• Design data lake and warehouse models, ingestion and ELT pipelines for batch, streaming and near real time needs using tools such as dbt, Airflow or Cloud Composer.
• Enable LLM, RAG and agentic AI scenarios using solid data and vector foundations, integrating Vertex AI and Snowflake capabilities where appropriate.
• Lead client workshops, solution design, sizing, effort estimation and proposal or SOW creation as part of presales cycles.
• Guide delivery teams through design reviews, code and pipeline best practices, CI/CD for data and ML and mentor engineers and junior architects.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).