Data Engineer ( Google Cloud Platform / Google BigQuery)

Overview

On Site
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 12 Month(s)
No Travel Required
Able to Provide Sponsorship

Skills

Data Enginnering
GCP ( Google Cloud)
Google BigQuery
DBT
Terraform
GIT
SQL / Python / Apache Spark

Job Details

Data Engineer (Google Cloud Platform / Google BigQuery)

  • Location: Dallas, TX or Little Rock, AR
  • Position is On-site 5 days/week.
  • Client : Financial
  • Contract : 12 + months
  • Open on c2c or w2

The client is seeking a mid to Sr. level Data Engineer, with experience in Google Big Query, Google Cloud Platform, ETL Pipeline, BI, Cloud Skills, Microsoft SQL with experience in both building and designing.

Job Description -

We are looking for a Google Cloud data engineer, who wants to collaborate in an agile team of peers developing cloud based analytics platform integrating data from broad amount of systems to enable next-gen analytical products.

The Data Engineering Google Cloud Platform (Google Cloud Platform) Engineer is responsible to develop and deliver effective cloud solutions for different business units. This position requires in-depth knowledge and expertise in Google Cloud Platform services, architecture, and best practices. They will collaborate with cross-functional teams to design, implement, and manage scalable and reliable cloud solutions. This position will also be responsible for driving innovation and staying up-to-date with the latest Google Cloud Platform technologies and trends to provide industry-leading solutions.

Responsibilities:

  1. You will directly work on the platform based on Google BigQuery and other Google Cloud Platform services to integrate new data sources and model the data up to the serving layer.
  2. Contribute to this is unique opportunity as the program is set-up to completely rethink reporting and analytics with Cloud technology.
  3. Collaborate with different business groups, users to understand their business requirements and design and deliver Google Cloud Platform architecture, Data Engineering scope of work
  4. You will work on a large-scale data transformation program with the goal to establish a scalable, efficient and future-proof data & analytics platform.
  5. Develop and implement cloud strategies, best practices, and standards to ensure efficient and effective cloud utilization.
  6. Work with cross-functional teams to design, implement, and manage scalable and reliable cloud solutions on Google Cloud Platform.
  7. Provide technical guidance and mentorship to the team to develop their skills and expertise in Google Cloud Platform.
  8. Contribute to multiyear data analytics modernization roadmap for the bank.
  9. Stay up-to-date with the latest Google Cloud Platform technologies, trends, and best practices and assess their applicability to client solutions.

Qualifications:

What will help you succeed:

  1. Bachelors University degree computer science/IT
  2. Master s in data Analytics/Information Technology/Management Information System (preferred)
  3. Strong understanding of data fundamentals, knowledge of data engineering and familiarity with core cloud concepts
  4. Must have good implementation experience on various Google Cloud Platform s Data Storage and Processing services such as Big Query, Dataflow, Bigtable, Data form, Data fusion, cloud spanner, Cloud SQL
  5. Must have programmatic experience of SQL, Python, Apache Spark
  6. At least 3-5 years of professional experience in building data engineering capabilities for various analytics portfolios with at least 2 years in Google Cloud Platform/Cloud based platform.

Your expertise in one or more of the following areas is highly valued:

  1. Google Cloud Platform, ideally with Google Big Query, Cloud Composer and Cloud Data Fusion, Cloud spanner, Cloud SQL
  2. Experience with legacy data warehouses (on SQL Server or any Relational Datawarehouse platform)
  3. Experience with our main tools DBT (Data Build Tool) , Terraform/Terragrunt, Git (CI/CD)
  4. Experience with a testing framework.
  5. Experience with Business Intelligence tools like PowerBI and/or Looker.

What sets you apart:

  1. Experience in complex migrations from legacy data warehousing solutions or on-prem Data Lakes to Google Cloud Platform
  2. Experience with building generic, re-usable capabilities and understanding of data governance and quality frameworks.
  3. Experience in building real-time ingestion and processing frameworks on Google Cloud Platform.
  4. Adaptability to learn new technologies and products as the job demands.
  5. Multi-cloud & hybrid cloud experience
  6. Any cloud certification (Preference to Google Cloud Platform Certifications)
  7. Experience working with Financial and Banking Industry
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.