Senior Cloud Data Architect

7 days ago


New York, New York, United States Tech Tammina Full time
Tech Tammina is seeking a highly experienced Data Engineer - GCP Specialist to join our team. This role offers an estimated annual salary of $250,000-$350,000 based on location and industry standards.

This position involves designing, developing, and maintaining data pipelines on Google Cloud Platform (GCP) for our company. The ideal candidate should have extensive experience in IT and data engineering, particularly with GCP in the financial sector. They should be proficient in managing and optimizing data storage, ensuring data security, and using Python and SQL for data manipulation. Strong collaboration skills are also required to work with various teams.

The project involves transforming raw data into valuable insights. Key responsibilities include:
  • Designing and developing data pipelines on GCP.
  • Implementing data security and access controls using GCP IAM and Cloud Security Command Center.
  • Data manipulation and querying using Python and SQL.
  • Distributed data processing with Apache Beam and Apache Spark.
We require 12+ years of IT experience, including 4+ years of recent experience with a major bank or brokerage house in the US, and 8+ years as a Data Engineer. Specific experience with GCP services like Dataflow, Dataproc, Pub/Sub, GCS, BigQuery, Cloud Storage, and Dataflow is necessary. Additionally, experience in data storage management and optimization with BigQuery, Cloud Storage, and Cloud SQL is essential.

The ideal candidate should possess the following skills:
  • GCP services: Dataflow, Dataproc, Pub/Sub, GCS, BigQuery, Cloud Storage, Cloud SQL.
  • Data security and access control principles.
  • Python & SQL for data manipulation and querying.
  • Apache Beam and Apache Spark.
  • Monitoring and troubleshooting with GCP's Stackdriver and Cloud Monitoring tools.
  • Automation of data processing tasks using scripting languages like Python.
  • Strong collaboration skills to work with data experts, analysts, and product teams.


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