Google Cloud Platform Data Architect / Senior Google Cloud Platform Data Engineer

Medinext Global LLC

United States

6 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Compensation

$150,000.0 - $200,000.0

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Airflow Big Data BigQuery Cloud Computing Cloud Computing Security Cloud Database Cloud Storage Code Review Computer Programming Databases

+43 more

Continuous Integration Data as a Services Directed Acyclic Graph (Directed Graphs) Data Architecture Information Engineering Data Fusion Data Governance Data Integration Extract Transform Load (ETL) Data Migration Data Security Data Systems Data Warehousing Data Flow Control Github Apache Hadoop Industry Standard Architecture Python (Programming Language) Cloud Services Cloudera SQL Databases Enterprise Data Management Data Processing Google Cloud Enterprise Software Applications Real Time Systems Snowflake Apache Spark Build Server Data Lakes AI Platforms Pyspark Kubernetes Information Technology Google Cloud Functions Data Management Cloud Migration Terraform Stream Processing Data Pipelines Apache Beam Jenkins Databricks

Job description

We are seeking an experienced Google Cloud Platform Data Architect / Senior Google Cloud Platform Data Engineer to design, develop, and implement scalable enterprise data platforms and cloud-based data solutions on Google Cloud Platform (Google Cloud Platform). The ideal candidate will have strong hands-on experience with Google Cloud Platform data services, cloud migration, data pipelines, data warehousing, real-time processing, and data architecture.

The successful candidate will work with engineering, analytics, data science, and business teams to build secure, reliable, and high-performance data solutions., * Design and implement enterprise data architectures on Google Cloud Platform.

Develop scalable batch and real-time data pipelines using Google Cloud Platform services.
Design and optimize data solutions using BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, and Cloud Composer.
Develop and manage ETL/ELT pipelines using Python, PySpark, SQL, and Apache Beam.
Build and maintain data lakes, data warehouses, and modern cloud data platforms.
Develop Airflow/Cloud Composer DAGs for data pipeline orchestration and scheduling.
Implement real-time streaming solutions using Pub/Sub and Dataflow.
Perform data migration from on-premises Hadoop and traditional data platforms to Google Cloud Platform.
Optimize BigQuery queries, storage, performance, and cloud costs.
Implement data quality, governance, security, and access-control standards.
Collaborate with data scientists and analytics teams to provide high-quality datasets.
Integrate Google Cloud Platform with enterprise applications, databases, APIs, and third-party platforms.
Implement CI/CD and Infrastructure as Code using tools such as Terraform and GitHub/Jenkins.
Monitor data pipelines and cloud workloads and troubleshoot production issues.
Participate in architecture discussions, technical design, documentation, and code reviews.
Provide technical leadership and mentor data engineering team members.

Requirements

Bachelor’s degree in Computer Science, Information Technology, Engineering, or related field.
10+ years of experience in data engineering, data architecture, or cloud data platforms.
Strong hands-on experience with Google Cloud Platform (Google Cloud Platform).
Excellent experience with:
BigQuery
Dataflow
Dataproc
Pub/Sub
Cloud Storage (GCS)
Cloud Composer / Apache Airflow
Strong programming experience with Python, PySpark, and SQL.
Experience designing data lakes, data warehouses, ETL/ELT pipelines, and dimensional data models.
Experience with large-scale data processing using Spark / Apache Beam.
Experience with real-time and batch data processing.
Experience with cloud migration and modernization projects.
Strong understanding of data security, governance, quality, and architecture best practices.

Preferred Qualifications

Experience with Vertex AI / Google Cloud AI services.
Experience with GKE/Kubernetes, Cloud Functions, Cloud Run, and Cloud Build.
Experience with Snowflake and/or Databricks.
Experience with Terraform, GitHub, Jenkins, and CI/CD.
Experience with Data Fusion, Dataform, DBT, or similar data integration tools.
Experience in healthcare, financial services, retail, or other enterprise environments.
Google Cloud Professional Data Engineer or Professional Cloud Architect certification is preferred.

Key Skills

Google Cloud Platform, Google Cloud Platform, Google Cloud Platform Data Architecture, BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Cloud Composer, Apache Airflow, Python, PySpark, SQL, Apache Beam, Spark, Data Engineering, Data Architecture, Data Lake, Data Warehouse, ETL, ELT, Data Modeling, Real-Time Data Streaming, Cloud Migration, Vertex AI, GKE, Kubernetes, Cloud Functions, Cloud Run, Terraform, GitHub, Jenkins, CI/CD, Snowflake, Databricks, Data Governance, Data Quality, Cloud Security, The ideal candidate is a senior Google Cloud Platform Data Architect/Data Engineer with strong hands-on experience building enterprise-scale data platforms on Google Cloud. Candidates with proven experience in BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer/Airflow, Python, PySpark, cloud migration, and data architecture will be highly preferred.