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Pivotal Solutions

Data Architect

Posted Yesterday
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Remote
Hiring Remotely in USA
Senior level
Remote
Hiring Remotely in USA
Senior level
Design and architect robust ETL/data pipelines on cloud platforms. Build and automate data ingestion and preprocessing using Spark/Databricks, AWS Glue, Airflow. Implement warehousing architectures (EDW, DM, ODS, MOLAP/ROLAP), ensure SQL-based data quality, use version control, and deliver tested production pipelines while communicating with stakeholders.
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This is a remote position.

Roles & Responsibilities


  • Strong verbal/written communication & facilitation skills. Ability to take a requirement document, work through any ambiguity and follow through to implementation independently
  • Strong analytical and problem-solving abilities
  • Strong work ethic, sense of ownership and a team player
  • Architect and design robust ETL processes using tools like Spark, Airflow, AWS Glue etc. to desired client specifications
  • Ability to analyze the data to identify the necessary pre-processing steps for the automated ETL processes
  • Solid understanding of SQL using databases like MS SQL Server, Redshift, etc.
  • Experience in Cloud Infrastructure (AWS, Azure, GCP)
  • Delivering the data pipeline with Quality and automated testing


Required Skills


  • Bachelor’s degree in computer science, information technology, or a related field.
  • Extensive knowledge of coding languages used to build data pipelines, such as Java, Scala, and/or Python
  • Experience with Databricks or Spark
  • Hands on experience building data pipelines in AWS using AWS Glue, Redshift, S3 buckets and other relevant technologies.
  • Proficiency in warehousing architecture techniques, including MOLAP, ROLAP, ODS, DM, and EDW.
  • Proven work experience as an ETL developer.
  • Experience using Source Code and Version Control systems like Git etc.
  • Strong project management skills.
  • Ability to analyze a company’s big-picture data needs.
  • Clear communication skills.
  • Ability to troubleshoot and solve complex technical problems.
  • Desire to continually keep up with advancements in data best practices


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