Silicontek Inc
GCP Lead Data Engineer
ā - Featured Role | Apply direct with Data Freelance Hub
This role is for a GCP Lead Data Engineer with 8-10 years of experience, focusing on advanced data architecture in a remote setting. Key skills include GCP, Python, SQL, and data governance. A Bachelor's or Master's in IT or Computer Science is required.
š - Country
United States
š± - Currency
$ USD
-
š° - Day rate
Unknown
-
šļø - Date
July 2, 2026
š - Duration
Unknown
-
šļø - Location
Remote
-
š - Contract
Unknown
-
š - Security
Unknown
-
š - Location detailed
United States
-
š§ - Skills detailed
#Airflow #Distributed Computing #Infrastructure as Code (IaC) #Data Security #Strategy #Vault #Data Architecture #Clustering #Libraries #GCP (Google Cloud Platform) #Logging #Security #Monitoring #Python #Dataflow #BigQuery #Compliance #Data Governance #Scala #BI (Business Intelligence) #Apache Beam #Data Integration #Leadership #Observability #Terraform #SQL (Structured Query Language) #Batch #Computer Science #DataOps #SaaS (Software as a Service) #GDPR (General Data Protection Regulation) #Automation #Code Reviews #Cloud #Data Ingestion #Data Vault #Snowflake #VPC (Virtual Private Cloud) #Data Modeling #Data Science #IAM (Identity and Access Management) #Data Engineering
Role description
Role-GCP Lead Data Engineer
Location-Remote
We are seeking a Senior Data Engineer with a distinguished background in Google Cloud Platform (GCP) to spearhead the evolution of our enterprise data ecosystem. With 8ā10 years of professional experience, the successful candidate will operate as a technical authority, designing and deploying sophisticated data architectures that bridge the gap between complex raw data and strategic business intelligence. This role demands a mastery of distributed computing, advanced Python development, and expert-level SQL optimization to ensure the integrity, scalability, and cost-efficiency of our global data assets.
Core Responsibilities
1. Architectural Strategy & System Design
Enterprise Framework Design: Conceptualize and implement end-to-end data architectures utilizing GCPās Modern Data Stack (BigQuery, Dataflow, Pub/Sub).
Scalable Data Modeling: Lead the development of high-performance data models (Star, Snowflake, Data Vault) optimized for multi-petabyte scale and high-concurrency analytics.
Hybrid & Multi-Cloud Strategy: Provide technical leadership on data integration strategies spanning GCP, on-premise systems, and third-party SaaS environments.
1. Advanced Engineering & Pipeline Automation
Distributed Processing: Engineer highly resilient, low-latency streaming and batch pipelines using Apache Beam (Dataflow) and Cloud Composer (Airflow).
Software Engineering Excellence: Develop reusable Python libraries and frameworks to standardize data ingestion, logging, and error-handling across the engineering team.
Infrastructure as Code (IaC): Drive operational maturity by managing cloud resources exclusively through Terraform, ensuring robust versioning and environment parity.
1. Data Governance, Security & Performance
System Optimization: Conduct deep-dive performance tuning of BigQuery environments, implementing partitioning, clustering, and slot management to optimize ROI.
Security & Compliance: Architect data security protocols including VPC Service Controls, IAM Least Privilege, and data masking/encryption to meet global compliance standards (GDPR, SOC2).
Observability: Establish comprehensive monitoring and alerting frameworks for data health, ensuring high availability and meeting stringent Service Level Objectives (SLOs).
1. Technical Leadership & Collaboration
Strategic Mentorship: Serve as a mentor to mid-level and junior engineers, conducting rigorous code reviews and promoting best practices in DataOps.
Stakeholder Alignment: Act as a primary technical liaison between Data Science, Business Intelligence, and Executive leadership to translate business goals into technical roadmaps.
Education
ā¢ Bachelors or Masters in Information Technology, Computer Science or relevant field.
Role-GCP Lead Data Engineer
Location-Remote
We are seeking a Senior Data Engineer with a distinguished background in Google Cloud Platform (GCP) to spearhead the evolution of our enterprise data ecosystem. With 8ā10 years of professional experience, the successful candidate will operate as a technical authority, designing and deploying sophisticated data architectures that bridge the gap between complex raw data and strategic business intelligence. This role demands a mastery of distributed computing, advanced Python development, and expert-level SQL optimization to ensure the integrity, scalability, and cost-efficiency of our global data assets.
Core Responsibilities
1. Architectural Strategy & System Design
Enterprise Framework Design: Conceptualize and implement end-to-end data architectures utilizing GCPās Modern Data Stack (BigQuery, Dataflow, Pub/Sub).
Scalable Data Modeling: Lead the development of high-performance data models (Star, Snowflake, Data Vault) optimized for multi-petabyte scale and high-concurrency analytics.
Hybrid & Multi-Cloud Strategy: Provide technical leadership on data integration strategies spanning GCP, on-premise systems, and third-party SaaS environments.
1. Advanced Engineering & Pipeline Automation
Distributed Processing: Engineer highly resilient, low-latency streaming and batch pipelines using Apache Beam (Dataflow) and Cloud Composer (Airflow).
Software Engineering Excellence: Develop reusable Python libraries and frameworks to standardize data ingestion, logging, and error-handling across the engineering team.
Infrastructure as Code (IaC): Drive operational maturity by managing cloud resources exclusively through Terraform, ensuring robust versioning and environment parity.
1. Data Governance, Security & Performance
System Optimization: Conduct deep-dive performance tuning of BigQuery environments, implementing partitioning, clustering, and slot management to optimize ROI.
Security & Compliance: Architect data security protocols including VPC Service Controls, IAM Least Privilege, and data masking/encryption to meet global compliance standards (GDPR, SOC2).
Observability: Establish comprehensive monitoring and alerting frameworks for data health, ensuring high availability and meeting stringent Service Level Objectives (SLOs).
1. Technical Leadership & Collaboration
Strategic Mentorship: Serve as a mentor to mid-level and junior engineers, conducting rigorous code reviews and promoting best practices in DataOps.
Stakeholder Alignment: Act as a primary technical liaison between Data Science, Business Intelligence, and Executive leadership to translate business goals into technical roadmaps.
Education
ā¢ Bachelors or Masters in Information Technology, Computer Science or relevant field.
