Job Details

ID #20100159
State Texas
City Dallas / fort worth
Job type Contract
Salary USD $75 - $80 75 - 80
Source DISYS - Digital Intelligence Systems, LLC
Showed 2021-09-23
Date 2021-09-15
Deadline 2021-11-13
Category Et cetera
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Google Cloud Platform Data Engineer

Texas, Dallas / fort worth, 75201 Dallas / fort worth USA

Vacancy expired!

Position: Google Cloud Platform Data Engineer

Location: Dallas, TX OR Tampa, FL

Duration: 12 - 30 Months
  • Google Cloud Platform Data Engineer Looking for a Big Data Engineer on Google Cloud Platform to help design, develop and maintain data engineering solutions to migrate data hosted on our on-prem platform to Google cloud Platform (Google Cloud Platform).
  • The engineer will design and program PB sized scalable data lake interfaces, micro services and web technologies that support ingesting and querying structured data.
  • Architect and program sophisticated distributed systems and high performance compute and data pipelines.
  • Enable mining and analyzing data to help AI leaders and researchers make data driven decisions for data collection, diversity, training, and evaluation.
  • Build and implement support for versioned, traceable, and immutable datasets in a data lake in a distributed and scalable manner.
  • Spend a majority of the time hands-on writing code and peer reviewing high performance, high quality, and well tested and well architected code.
MUST HAVE SKILLS (Most Important):
  • Certified Google Cloud Data Engineer/Architect Bachelor’s degree with 3-5+ years of experience in Data Engineering/BI areas with at least 2 years data engineering on Google Cloud Platform·
  • Experience working in Google Cloud Platform based Big Data deployments (Batch/Real-Time) leveraging Big Query, Big Table, Google Cloud Storage, PubSub, Data Fusion, Dataflow, Dataproc, etc.
  • Experience developing and deploying ETL / ELT processes and documentation including physical data model, source to target mappings, ETL / ELT packages (Matillion, Fivetran, Spark, Google Data Fusion, etc.)
  • Demonstrated mastery in Google BigQuery
DESIRED SKILLS:
  • Strong knowledge of Hadoop, HDFS, Hive, Spark, Spark Streaming and Presto Strong knowledge on Google cloud storage Data lifecycle management
  • Strong knowledge on BIGQuery Slots management
  • Cost optimization for Dataproc workload management
  • Demonstrated mastery in cloud database concepts and large-scale cloud data warehouse and lake implementations using Big Data Tools: BigQuery, Cloud Dataflow, Cloud Proc, Cloud Pub/Sub, Cloud Composer, Google Data Studio, Cloud functions, Google Cloud Storage Implement solutions for structured, semi-structured, and unstructured data sources, relational and non-relational databases.
  • Advanced Java/Python coding skills Experience with CI-CD pipelines for promoting big data release deployments and designing log monitoring features ((e.g. JIRA, GitHub, Jenkins, Nexus, Artifactory)
  • Experience in data visualization tools like Kibana, Grafana, Tableau and associated architectures.
JOB DUTIES:
  • Design and build data engineering solutions using Google Cloud Platform (Google Cloud Platform) services: BigQuery, DataFlow, Pub/Sub, BigTable, Data Fusion, DataProc.
  • Data modeling and schema design that will range across multiple business domains within the cloud for large enterprise data warehouse and data lakes solutions.
  • Extracting, Loading, Transforming, cleaning, and validating data using cloud ETL/ELT tools
  • Designing data engineering pipelines and architectures for data processing Partner with multiple client stakeholders including partners, business users, BI and Analytics teams.
  • Work with teams to conduct training workshops to identify data sources, flows, and requirements.
  • Periodically update senior management with the status of the project with excellent written and verbal communication skills
EDUCATION/CERTIFICATIONS: Bachelor’s degree with 3-5+ years of experience in Data Engineering/BI areas with at least 2 years data engineering on Google Cloud Platform·

Vacancy expired!

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