Google Cloud Data Architect & IAM Data Modernization

Role: Google Cloud Data Architect – IAM Data Modernization

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.

What You'll Do:

DevOps / CI‑CD

• Experience
implementing CI/CD pipelines for data and analytics workloads
• Familiarity with
Git‑based 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

• Hands‑on 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 large‑scale 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\-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

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 solution‑architecture skills

Expertise You'll Bring:

* 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

Flexible work from home options available.