What are the responsibilities and job description for the Google Cloud Data Architect & IAM Data Modernization position at Vytwo Technologies Inc.?
Role: Google Cloud Data Architect – IAM Data Modernization
Location: Dallas, TX / Charlotte, NC/ Iselin, NJ, / Chandler, AZ / Ohio, Delaware (Hybrid)
DevOps / CI‑CD
Security, Privacy & Compliance
Location: Dallas, TX / Charlotte, NC/ Iselin, NJ, / Chandler, AZ / Ohio, Delaware (Hybrid)
- Must be a US Citizen/ GC only About Position: Identity & Access Management (IAM) Data Modernization – migration of an on‑premises SQL data warehouse to a target‑state Data Lake on Google Cloud (GCP), enabling metrics & reporting, advanced analytics, and GenAI use cases (natural language querying, accelerated summarization, cross‑domain trend analysis) leveraging PySpark‑based processing, cloud‑native DevOps CI/CD pipelines, and containerized deployments on OpenShift (OCP) to deliver scalable, secure, and high‑performance data solutions.
DevOps / CI‑CD
- Experience implementing CI/CD pipelines for data and analytics workloads
- Familiarity with Git‑based 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 GCP Secret Manager
- Ownership of observability, SLOs, dashboards, alerts, and runbooks
- Proficiency in logging, monitoring, and alerting for data pipelines and platform reliability
- Hands‑on 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 (GCP)
- Experience with Data Lakes, data warehousing, and large‑scale 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 GCP-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
- Hands-on experience with workflow orchestration tools (Cloud Composer / Airflow)
- Ability to design robust error handling, replay, and backfill mechanisms
- Experience developing scalable batch and streaming pipelines using Dataflow (Apache Beam) and/or Spark (Dataproc)
- 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
- Expertise in BigQuery performance optimization and data serving patterns
- Experience building semantic layers and governed metrics for consistent analytics
- Familiarity with BI integration, access controls, and dashboard standards
- Understanding of data exposure patterns via views, APIs, or curated datasets
- Experience implementing data catalogs, metadata management, and ownership models
- Understanding of data lineage for auditability and troubleshooting
- Strong focus on data quality frameworks, including validation, freshness checks, and alerting
- Experience defining and enforcing data contracts, schemas, and SLAs
Security, Privacy & Compliance
- Hands-on experience implementing fine-grained access controls for BigQuery and GCS
- Experience with Sprint planning and helping team technically.
- Strong stakeholder communication and solution‑architecture skills
- Experience: [10–14] years in DevOps and Data Architecture, 5 years designing on Pyspark/GCP/OCP at scale; prior on‑prem → cloud migration a must.
- Education: Bachelor’s/Master’s in Computer Science, Information Systems, or equivalent experience.
- Certifications:Google Cloud Professional Cloud Architect/DevOps/OCP (required or within 3 months). Plus: Professional Data Engineer, Security Engineer