Senior Data Engineer – GCP
Senior Data Engineer – Google Cloud Platform (GCP)
Location:
LATAM
- Remote Employment Type: Full-Time Contractor Project Duration: Initial 3-month engagement Monthly Compensation: USD 3,950–4,500
About Us
Latam Digital Hub by Stefanini is part of a global technology services organization delivering innovative digital transformation and nearshore solutions to international clients. We connect highly skilled professionals across Latin America with enterprise technology initiatives, offering opportunities to work with distributed teams, modern technologies, and complex business environments.
About the Role
We are looking for an experienced Senior Data Engineer with strong hands-on expertise in Google Cloud Platform (GCP) to support a large-scale data engineering initiative for an international enterprise client. In this role, you will design, develop, and optimize production-grade batch and streaming data pipelines while contributing to the reliability, scalability, and continuous improvement of cloud-based data solutions. You will serve as a key technical contributor within a distributed engineering team, collaborating with architects, product owners, and business stakeholders to translate requirements into production-ready solutions. The position also involves establishing engineering best practices, providing technical guidance, and mentoring junior and mid-level engineers. We are looking for someone who combines strong engineering expertise with hands-on problem-solving, technical ownership, and the ability to deliver in a collaborative Agile environment.
Key Responsibilities
• Design, develop, and maintain scalable batch and streaming data pipelines using Google Cloud Platform technologies, including BigQuery, Dataflow, Cloud Storage, and Pub/Sub.
• Build and optimize data transformation workflows using Dataform, SQL, and related technologies.
• Develop and maintain event-driven data processing solutions using Confluent Kafka and/or Google Pub/Sub.
• Implement and manage data pipeline orchestration using Apache Airflow.
• Collaborate with architects, product owners,
analysts, and engineering teams to translate business requirements into reliable technical solutions.
• Optimize BigQuery workloads, ensuring performance, scalability, cost efficiency, and data quality.
• Monitor production pipelines, troubleshoot incidents, conduct root-cause analysis, and implement sustainable solutions.
• Establish and enforce engineering standards, including coding practices, peer reviews, automated testing, CI/CD, and technical documentation.
• Provide technical mentorship and guidance to junior and mid-level engineers.
• Implement data security, governance, lineage, and access-control practices across data engineering solutions.
• Participate in Agile ceremonies, including sprint planning, daily stand-ups, backlog refinement, and retrospectives.
• Identify opportunities to improve data architecture, engineering processes, and platform reliability. Requirements
• 7+ years of professional experience in Data Engineering, Big Data Engineering, or Data Architecture, including hands-on development of production-scale solutions.
• Extensive hands-on experience with Google Cloud Platform (GCP), particularly BigQuery, Dataflow, Cloud Storage, and Pub/Sub.
• Expert-level SQL skills, including complex transformations, query optimization, and large-scale data processing.
• Proven experience designing, developing, and maintaining batch and real-time streaming pipelines.
• Production experience with Confluent Kafka or Google Pub/Sub.
• Strong experience with Apache Airflow for workflow orchestration.
• Hands-on experience with Dataform or similar SQL-based transformation frameworks, such as dbt.
• Proficiency in Python or Java for pipeline development, automation, and data processing.
• Experience with at least one relational database, such as PostgreSQL, Oracle, or SQL Server.
• Solid understanding of data ingestion, data warehousing, ETL/ELT processes, and medallion or layered data architectures.
• Experience troubleshooting production issues, monitoring pipeline performance, and maintaining data reliability.
• Understanding of data quality, security, governance, and engineering best practices.
• Experience working in Agile/Scrum environments with geographically distributed teams.
• Ability to provide technical guidance, conduct code reviews, and mentor other engineers. Nice to Have
• Google Cloud Professional Data Engineer certification.
• Experience with managed data ingestion tools such as Fivetran.
• Familiarity with data catalog and lineage platforms, including Alation.
• Experience with data security and governance solutions such as Immuta and native BigQuery access controls.
• Knowledge of Data Mesh principles and data product architecture.
• Experience with additional analytics and data platforms such as Databricks or Palantir.
• Exposure to generative AI, AI agents, or AI-powered data engineering workflows.
• Experience with Git, Cloud Build, Jenkins, or other CI/CD technologies.
• Familiarity with monitoring and observability tools such as Cloud Monitoring, Grafana, or Prometheus.
• Additional certifications in cloud technologies, data engineering, or analytics. Why Join Us?
• 100% Remote Opportunity: Work from anywhere in Latin America while collaborating with international teams.
• International Exposure: Contribute to enterprise-level technology initiatives supporting global business operations.
• Modern Technology Stack: Work extensively with Google Cloud Platform, modern data architectures, and scalable data processing technologies. Important: This is an initial 3-month, full-time independent contractor engagement, subject to final project confirmation.
Location:
LATAM
- Remote Employment Type: Full-Time Contractor Project Duration: Initial 3-month engagement Monthly Compensation: USD 3,950–4,500
About Us
Latam Digital Hub by Stefanini is part of a global technology services organization delivering innovative digital transformation and nearshore solutions to international clients. We connect highly skilled professionals across Latin America with enterprise technology initiatives, offering opportunities to work with distributed teams, modern technologies, and complex business environments.
About the Role
We are looking for an experienced Senior Data Engineer with strong hands-on expertise in Google Cloud Platform (GCP) to support a large-scale data engineering initiative for an international enterprise client. In this role, you will design, develop, and optimize production-grade batch and streaming data pipelines while contributing to the reliability, scalability, and continuous improvement of cloud-based data solutions. You will serve as a key technical contributor within a distributed engineering team, collaborating with architects, product owners, and business stakeholders to translate requirements into production-ready solutions. The position also involves establishing engineering best practices, providing technical guidance, and mentoring junior and mid-level engineers. We are looking for someone who combines strong engineering expertise with hands-on problem-solving, technical ownership, and the ability to deliver in a collaborative Agile environment.
Key Responsibilities
• Design, develop, and maintain scalable batch and streaming data pipelines using Google Cloud Platform technologies, including BigQuery, Dataflow, Cloud Storage, and Pub/Sub.
• Build and optimize data transformation workflows using Dataform, SQL, and related technologies.
• Develop and maintain event-driven data processing solutions using Confluent Kafka and/or Google Pub/Sub.
• Implement and manage data pipeline orchestration using Apache Airflow.
• Collaborate with architects, product owners,
analysts, and engineering teams to translate business requirements into reliable technical solutions.
• Optimize BigQuery workloads, ensuring performance, scalability, cost efficiency, and data quality.
• Monitor production pipelines, troubleshoot incidents, conduct root-cause analysis, and implement sustainable solutions.
• Establish and enforce engineering standards, including coding practices, peer reviews, automated testing, CI/CD, and technical documentation.
• Provide technical mentorship and guidance to junior and mid-level engineers.
• Implement data security, governance, lineage, and access-control practices across data engineering solutions.
• Participate in Agile ceremonies, including sprint planning, daily stand-ups, backlog refinement, and retrospectives.
• Identify opportunities to improve data architecture, engineering processes, and platform reliability. Requirements
• 7+ years of professional experience in Data Engineering, Big Data Engineering, or Data Architecture, including hands-on development of production-scale solutions.
• Extensive hands-on experience with Google Cloud Platform (GCP), particularly BigQuery, Dataflow, Cloud Storage, and Pub/Sub.
• Expert-level SQL skills, including complex transformations, query optimization, and large-scale data processing.
• Proven experience designing, developing, and maintaining batch and real-time streaming pipelines.
• Production experience with Confluent Kafka or Google Pub/Sub.
• Strong experience with Apache Airflow for workflow orchestration.
• Hands-on experience with Dataform or similar SQL-based transformation frameworks, such as dbt.
• Proficiency in Python or Java for pipeline development, automation, and data processing.
• Experience with at least one relational database, such as PostgreSQL, Oracle, or SQL Server.
• Solid understanding of data ingestion, data warehousing, ETL/ELT processes, and medallion or layered data architectures.
• Experience troubleshooting production issues, monitoring pipeline performance, and maintaining data reliability.
• Understanding of data quality, security, governance, and engineering best practices.
• Experience working in Agile/Scrum environments with geographically distributed teams.
• Ability to provide technical guidance, conduct code reviews, and mentor other engineers. Nice to Have
• Google Cloud Professional Data Engineer certification.
• Experience with managed data ingestion tools such as Fivetran.
• Familiarity with data catalog and lineage platforms, including Alation.
• Experience with data security and governance solutions such as Immuta and native BigQuery access controls.
• Knowledge of Data Mesh principles and data product architecture.
• Experience with additional analytics and data platforms such as Databricks or Palantir.
• Exposure to generative AI, AI agents, or AI-powered data engineering workflows.
• Experience with Git, Cloud Build, Jenkins, or other CI/CD technologies.
• Familiarity with monitoring and observability tools such as Cloud Monitoring, Grafana, or Prometheus.
• Additional certifications in cloud technologies, data engineering, or analytics. Why Join Us?
• 100% Remote Opportunity: Work from anywhere in Latin America while collaborating with international teams.
• International Exposure: Contribute to enterprise-level technology initiatives supporting global business operations.
• Modern Technology Stack: Work extensively with Google Cloud Platform, modern data architectures, and scalable data processing technologies. Important: This is an initial 3-month, full-time independent contractor engagement, subject to final project confirmation.