Senior Google Cloud Platform Data Engineers

Title: Senior Google Cloud Platform Data Engineers

Work Location: 499 Park Ave NYC NY (Midtown)

Duration: 1yr (Renewable)

Start: ASAP

Skills Needed:

• Must have 12 year plus of IT experience.
• Must have 4+ years of ‘Recent’ experience (With in last 7 years / since 2018) working for a Major Bank or Brokerage house in the US working with Google Cloud Platform.
• Must have 8 plus years of experience as a Data Engineer designing, developing, and deploying data pipelines.
• Must have 5 plus years of experience with Python & SQL for data manipulation and querying
• Must have 5 plus years of experience with the distributed data processing framework Apache Beam and Apache Spark.
• Must have 5 plus years of experience with Google Cloud Platform services Dataflow, Dataproc, and Pub/Sub,
• Must have 5 plus years of experience with core data services GCS, BigQuery, Cloud Storage, and Dataflow.
• Must have 5 plus years experience managing and optimizing data storage Big Query, Cloud Storage, and Cloud SQL.
• Must have 5 plus years implementing data security and access controls using Google Cloud Platform''s Identity and Access Management (IAM) and Cloud Security Command Center.
• Experience with data security and access control principles

The Job:

Senior Google Cloud Platform (Google Cloud Platform) Data Engineer to play a critical role in designing, developing, and maintaining robust data pipelines that transform raw data into valuable insights for our organization.

• Design, develop, and maintain data pipelines using Google Cloud Platform services like Dataflow, Dataproc, and Pub/Sub, in addition to developing and implementing data ingestion and transformation processes using tools like Apache Beam and Apache Spark.
• Manage and optimize data storage solutions on Google Cloud Platform, including Big Query, Cloud Storage, and Cloud SQL, while implementing data security and access controls using Google Cloud Platform''s Identity and Access Management (IAM) and Cloud Security Command Center.
• Monitor and troubleshoot data pipelines and storage solutions using Google Cloud Platform''s Stackdriver and Cloud Monitoring tools.
• Collaborate with data experts, analysts, and product teams to understand data needs and deliver effective solutions.
• Automate data processing tasks using scripting languages like Python.