Google Cloud Data Architect & IAM Data Modernization in Prosper

Job DescriptionJob DescriptionRole: Google Cloud Data Architect IAM Data Modernization
Location: Dallas, TX / Charlotte, NC/ Iselin, NJ, / Chandler, AZ / Ohio, Delaware (Hybrid)

*Must be a US / GC only
About Position:
& Access Management (IAM) Data Modernization migration of an onpremises SQL data warehouse to a targetstate Data Lake on Google Cloud (GCP), enabling metrics & reporting, advanced analytics, and GenAI use cases (natural querying, accelerated summarization, crossdomain trend analysis) leveraging PySparkbased processing, cloudnative DevOps CI/CD pipelines, and containerized deployments on OpenShift (OCP) to deliver scalable, secure, and highperformance data solutions.

What You'll Do:
DevOps / CICD

• Experience implementing CI/CD pipelines for data and analytics workloads
• Familiarity with Gitbased source control, build automation, and deployment strategies

Containers & Platform

• 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

Big Data & Processing

• Handson experience with PySpark for ETL/ELT, data transformation, and performance optimization
• Solid understanding of distributed data processing concepts

Data & Cloud Architecture

• Strong experience designing data platforms on Google Cloud Platform (GCP)
• Experience with Data Lakes, data warehousing, and largescale migration programs

Data Lake Architecture & Storage

• 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

Data Ingestion & Orchestration
Experience building batch and streaming ingestion pipelines using GCP- 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

Data Processing & Transformation
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

Analytics & Data Serving
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

Data Governance, Quality & Metadata
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

Good to have
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 solutionarchitecture skills

Expertise You'll Bring:

• Experience: [1014]+ years in DevOps and Data Architecture, 5+ years designing on Pyspark/GCP/OCP at scale; prior onprem cloud migration a must.
• Education: Bachelors/Masters 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

Flexible work from home options available.