Google Cloud Platform Data Engineer

Isolve Technology Inc

Charlotte, NC, United States

3 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Agile Methodology Data Analysis Automation of Tests Batch Processing Big Data BigQuery Continuous Integration Serialization Data Systems Software Debugging

+26 more

Data Flow Control Apache Hadoop Hadoop Distributed File System Apache Hive JSON Kerberos (Protocol) MapR (Big Data) Microsoft SQL Server SQL Azure MongoDB NoSQL Scrum Methodology E2e Testing Cloudera SQL Databases System Testing Teradata SQL Extensible Markup Language (XML) Google Cloud Apache Spark Pyspark Apache Flink Avro Apache Kafka Data Management Restful APIs

Job description

Design, code, test, debug, and document technology solutions for complex projects and programs.
Review and analyze large-scale technology solutions to align with tactical and strategic business objectives, as well as enterprise technological environments.
Evaluate and develop companywide best practices for engineering and technology solutions, ensuring alignment with industry standards and new technologies.
Collaborate with key technical experts and senior technology teams to resolve complex technical challenges and meet project goals.
Contribute to the development of Data Mesh capabilities to improve data accessibility across disparate platforms such as Hadoop, Teradata, and SQL Servers.
Support Data Science functions by preparing pre-work required for data exploration and analysis.
Support System Testing, User Acceptance Testing (UAT), and end-to-end testing activities; develop test automation for batch processes and APIs within a CI/CD environment.
Work with Agile methodologies, writing user stories, and participating in Agile ceremonies.

Requirements

Extensive experience designing and delivering data solutions in Google Cloud Platform (Google Cloud Platform), leveraging services such as DataProc, DataFlow, BigQuery, and other Google Cloud Platform tools.
Expertise in Big Data platforms (e.g., MapR, Cloudera) using technologies like HDFS, Spark, PySpark, and Hive.
Proficiency in event-driven solutions using Java, REST APIs, Apache Flink, and Kafka technologies.
Experience with relational and NoSQL databases, including MongoDB, SQL Server, Atlas, and Azure SQL.
Strong familiarity with wire formats such as XML, JSON, Avro, and CSV, along with serialization/deserialization techniques.
Knowledge of security protocols (e.g., Kerberos, JWT) and their integration into data platforms and solutions.
Solid understanding of Agile methodologies, including writing user stories and participating in ceremonies such as sprint planning and retrospectives.