Data Architect

Title: Google Cloud Data Architect - IAM Data Modernization Location: Dallas, TX ( Hybrid Onsite) Duration: Long Term Contract Job description:- Required Skills:- 1. 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 Bl consumption 1. 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 1. Data Processing & Transformation • Experience developing scalable batch and streaming pipelines using Dataflow (Apache Beam) and/or Spark (Datapro6) • 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 1. 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 1. 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 • Experience denning and emorcing data contracts, schemas, and SLAS • Familiarity with audit logging and compliance readiness 1. Cloud Platform Management • Strong hands-on experience with Google Cloud Platform (GCP), including project setup, environment separation, billing, quotas, and cost controls • Expertise in IAM and security best practices, including least-privilege access, service accounts, and role-based access • Solid understanding of VPC networking, private access patterns, and secure service connectivity • Experience with encryption and key management (KMS, CMEK) and security auditing 1. DevOps, Platform & Reliability • 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 Qualifications Experience: [10-14] + years in data engineering/architecture, 5+ years designing on GCP 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 (required or within 3 months). Plus: Professional Data Engineer, Security Engineer.