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GCP Data Engineer

Remote:

Full Remote

Contract:

Full time

Work from:

United States

Offer summary

Qualifications:

Proficient in Python for data manipulation, Experience with GCP tools like BigQuery and Dataflow, Strong SQL skills for data management, Hands-on experience with ETL/ELT pipelines, Familiarity with data modeling and warehousing principles.

Key responsabilities:

Design, develop, and maintain ETL/ELT pipelines
Implement data warehousing solutions on GCP
Optimize data pipelines for performance and scalability
Collaborate with stakeholders to address data needs
Ensure data quality and enforce governance best practices

Elfonze Technologies Scaleup https://www.elfonze.com/

201 - 500 Employees

See more Elfonze Technologies offers

Job description

This is a remote position.

Key Responsibilities:

Design, develop, and maintain ETL/ELT pipelines using Python and GCP data services.
Implement data warehousing solutions on GCP, including data ingestion, transformation, and storage strategies.
Optimize data pipelines and infrastructure for performance, scalability, and reliability.
Collaborate with data scientists, analysts, and stakeholders to understand data needs and translate requirements into technical solutions.
Monitor data quality, troubleshoot issues, and ensure accuracy across systems.
Implement best practices in data governance, security, and compliance on GCP.
Develop data processing workflows using GCP services, such as Dataflow, BigQuery, and Pub/Sub.
Continuously improve data pipeline architecture and look for ways to optimize processes.

Mandatory Skills and Qualifications:

Python Programming: Proficiency in Python for data manipulation, ETL/ELT, and automation.
GCP Data Engineering Services: Experience with key GCP tools such as BigQuery, Dataflow, Dataproc, Cloud Composer, and Pub/Sub.
SQL Proficiency: Strong SQL skills for querying, analyzing, and managing data in cloud data warehouses.
ETL/ELT Development: Hands-on experience designing and building ETL/ELT pipelines for large datasets.
Data Modeling: Familiarity with data modeling concepts and best practices for structured and semi-structured data.
Data Warehousing: Understanding of data warehousing principles and experience with cloud-based data warehouses, particularly BigQuery.
Version Control: Experience using Git or other version control systems.
Data Quality and Monitoring: Proficiency in ensuring data accuracy and implementing data validation/testing practices.

Preferred Skills (Not Mandatory):

Experience with Apache Spark or other distributed data processing frameworks.
Familiarity with Terraform or other Infrastructure-as-Code (IaC) tools for GCP resource provisioning.
Knowledge of CI/CD practices and tools for data engineering.
Google Cloud certifications (e.g., Professional Data Engineer).