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Data Architect – GCP
Data & AIRemoteContractID: REQ-43635
N2P Systems
Denver, CO, USA or Remote8+ years$55 - $60 USDPosted 2 weeks ago
Role Overview
## Role Overview
KANINI is seeking an experienced Data Architect with deep expertise in Google Cloud Platform and modern enterprise data architecture. The role focuses on designing scalable, reliable, and cost-efficient data solutions across batch and real-time workloads. The successful candidate will bring strong hands-on expertise in BigQuery, PySpark, Dataflow, Airflow, Python, and SQL, combined with a strong understanding of cloud security, governance, performance optimization, and CI/CD practices.
## Key Responsibilities
- Design, develop, and maintain scalable batch and real-time data pipelines on GCP.
- Implement and manage Medallion Architecture across Bronze, Silver, and Gold data layers.
- Build high-performance data transformations using Python and PySpark.
- Develop and optimize complex SQL queries for analytical workloads.
- Design, implement, and tune BigQuery solutions including partitioning, clustering, and query optimization.
- Develop and deploy data pipelines using Cloud Dataflow.
- Orchestrate data workflows using Cloud Composer and Apache Airflow.
- Manage enterprise data storage and lifecycle using Google Cloud Storage.
- Implement Git-based version control and CI/CD practices for data engineering workflows.
- Apply GCP IAM, security controls, and governance best practices to enterprise data solutions.
- Optimize data platforms for performance, scalability, reliability, and cost efficiency.
- Contribute to data governance, data quality, warehousing, and data lake initiatives.
## Project Goals
- Build scalable enterprise-grade GCP data architecture supporting both batch and real-time processing.
- Establish robust Medallion Architecture and optimized BigQuery workloads for analytical use cases.
- Improve pipeline reliability, orchestration, deployment automation, security, governance, and overall platform efficiency.
Key Responsibilities
- Design, develop, and maintain scalable batch and real-time data pipelines on GCP.
- Implement and manage Medallion Architecture across Bronze, Silver, and Gold data layers.
- Build high-performance data transformations using Python and PySpark.
- Develop and optimize complex SQL queries for analytical workloads.
- Design, implement, and tune BigQuery solutions including partitioning, clustering, and query optimization.
- Develop and deploy data pipelines using Cloud Dataflow.
- Orchestrate data workflows using Cloud Composer and Apache Airflow.
- Manage enterprise data storage and lifecycle using Google Cloud Storage.
- Implement Git-based version control and CI/CD practices for data engineering workflows.
- Apply GCP IAM, security controls, and governance best practices to enterprise data solutions.
- Optimize data platforms for performance, scalability, reliability, and cost efficiency.
- Contribute to data governance, data quality, warehousing, and data lake initiatives.
- ## Project Goals
- Build scalable enterprise-grade GCP data architecture supporting both batch and real-time processing.
- Establish robust Medallion Architecture and optimized BigQuery workloads for analytical use cases.
- Improve pipeline reliability, orchestration, deployment automation, security, governance, and overall platform efficiency.
Required Skills & Qualifications
- Strong proficiency and experience with Google Cloud Platform (GCP)
- Strong proficiency and experience with BigQuery
- Strong proficiency and experience with Medallion Architecture
- Strong proficiency and experience with Python
- Strong proficiency and experience with PySpark
- Strong proficiency and experience with Advanced SQL
- Strong proficiency and experience with Cloud Dataflow
- Strong proficiency and experience with Cloud Composer / Apache Airflow
- Strong proficiency and experience with Google Cloud Storage (GCS)
- Strong proficiency and experience with Git and CI/CD
- Strong proficiency and experience with GCP IAM
- Strong proficiency and experience with Data Architecture / Data Engineering Experience
- Strong proficiency and experience with Cloud Composer (Apache Airflow)
- Strong proficiency and experience with Git
- Strong proficiency and experience with CI/CD
Target Tech Stack
Google Cloud Platform (GCP)BigQueryMedallion ArchitecturePythonPySparkAdvanced SQLCloud DataflowCloud Composer / Apache AirflowGoogle Cloud Storage (GCS)Git and CI/CDGCP IAMData Architecture / Data Engineering ExperienceEnterprise Data PlatformsData Warehousing and Data LakesReal-Time Streaming FrameworksData Governance and Data QualityAgile/ScrumSQLCloud ComposerApache AirflowGitCI/CDCloud Data GovernanceData SecurityData WarehousingData LakesReal-Time Data ProcessingData QualityCloud Composer (Apache Airflow)Large-scale enterprise data platformsData lake architectureData governance frameworksData quality frameworksAgile/Scrum methodologies
Quick Details
- Location
- Denver, CO, USA or Remote
- Employment Type
- Contract
- Work Arrangement
- Remote
- Experience Level
- 8+ years
- Compensation
- $55 - $60 USD
- Domain Focus
- Data & AI
- Requisition Ref
- REQ-43635
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