Role overview
INTENTO ANALYTICS is hiring for the Google Cloud Platform Data Architect role in Dallas, Texas, US. It is full-time, Mid-level level, in the Tech sector. It was posted 5/21/2026.
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- Role
- Google Cloud Platform Data Architect
- Company
- INTENTO ANALYTICS
- Location
- Dallas, Texas, US
- Work mode
- On-site
- Employment
- Full-time
- Seniority
- Mid-level
- Sector
- Tech
- Posted
- 5/21/2026
Description
Job Title: Google Cloud Data Architect IAM Data Modernization
Location: Dallas, TX / Charlotte, NC/ Iselin, NJ, / Chandler, AZ (Hybrid 4 days office)
Job Description
Bachelors or relevant degree with 10 14+ years in DevOps and Data Architecture, 5+ years designing on Pyspark/Google Cloud Platform/OCP at scale; prior on prem cloud migration a must.
Certifications: Google Cloud Professional Cloud Architect/DevOps/OCP (required or within 3 months). Plus: Professional Data Engineer, Security Engineer.
Experience implementing CI/CD pipelines for data and analytics workloads
Familiarity with Gitbased source control, build automation, and deployment strategies
Experience with OpenShift Container Platform (OCP) for deploying data workloads and services
Understanding of containerized architecture, scaling, and environment management
Proven ability to build CI/CD pipelines for data and infrastructure workloads
Experience managing secrets securely using Google Cloud Platform Secret Manager
Ownership of observability, SLOs, dashboards, alerts, and runbooks
Proficiency in logging, monitoring, and alerting for data pipelines and platform reliability
Handson experience with PySpark for ETL/ELT, data transformation, and performance optimization
Solid understanding of distributed data processing concepts
Strong experience designing data platforms on Google Cloud Platform (Google Cloud Platform)
Experience with Data Lakes, data warehousing, and largescale migration programs
Proven experience designing and implementing data lake architectures (e.g., Bronze/Silver/Gold or layered models).
Strong knowledge of Cloud Storage (GCS) design, including bucket layout, naming conventions, lifecycle policies, and access controls
Experience with Hadoop/HDFS architecture, distributed file systems, and data locality principles
Hands-on experience with columnar data formats (Parquet, Avro, ORC) and compression techniques
Expertise in partitioning strategies, backfills, and large-scale data organization
Ability to design data models optimized for analytics and BI consumption
Experience building batch and streaming ingestion pipelines using Google Cloud Platform-native services
Knowledge of Pub/Sub-based streaming architectures, event schema design, and versioning
Strong understanding of incremental ingestion and CDC patterns, including idempotency and deduplication
Strong proficiency in BigQuery SQL, including query optimization, partitioning, clustering, and cost control.
Hands-on experience with Hadoop MapReduce and ecosystem tools (Hive, Pig, Sqoop)
Advanced Python programming skills for data engineering, including testing and maintainable code design
Experience managing schema evolution while minimizing downstream impact
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