Must have LinkedIn

Title : GCP Data Engineer

Location : Remote ( need to work in Est timezone )

Duration : till end of this year and will have more extensions

GCP ACTIVE CERTIFICAION IS MUST HAVE

What You'll Do:

• Design, develop, and optimize data pipelines, architectures, and data sets in Google Cloud using tools such as BigQuery and DBT.
• Use SQL and DBT for data transformation and manipulation, developing complex SQL queries and implementing optimization techniques for improved performance.
• Utilize your expertise in Python to automate data pipeline processes, ensuring accuracy and efficiency.
• Collaborate with our team of data analysts and data scientists, providing them with clean, reliable data for their analytical work.
• Ensure data governance and security practices are applied across all data initiatives.
• Conduct regular reviews and tests of our data systems to ensure data integrity and quality.
• Stay up-to-date with industry trends and innovations, continuously improving and expanding your knowledge and skills.

What You Have:

• Google Cloud Certification (Professional Data Engineer)
• Deep expertise in DBT (Data Build Tool) for defining, testing, and documenting data transformations in BigQuery.
• Proficiency in creating and maintaining DBT models, understanding the use of macros, sources, and snapshots.
• Understanding of advanced DBT concepts like incremental models, custom schemas, and the use of variables.
• Experience with DBT Cloud, including setting up deployments, automated tests, and version control.
• Outstanding proficiency in SQL, with the ability to write complex, efficient queries for data extraction and transformation.
• Extensive experience with SQL optimization techniques, aiming to improve query performance and database scalability.
• Knowledge of advanced SQL concepts like window functions, common table expressions (CTEs), and stored procedures.
• Extensive experience in Google Cloud, including hands-on experience with Google Cloud data services such as BigQuery, Pub/Sub, Dataflow, and Dataproc.
• Proven ability to design and implement Google Cloud-based data architectures, adhering to best practices for security, performance, and reliability.
• Solid understanding of data warehousing concepts and data modeling principles.
• Proficient in Python for data automation tasks.
• Understanding of data governance and security practices.
• Google Cloud Certification - Professional Data Engineer
• Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders.
• Excellent problem-solving skills and attention to detail.