Bachelor's in Computer Science, Computer Engineering, or related field.
Experience with Data Warehousing, Operational Data Store, Data technologies and ETL solutions.
8+ years of experience in ETL (IBM DataStage), SQL, UNIX/Linux scripting, and Big Data distributed systems.
4+ years of experience working with Teradata (Vantage), SQL Server, Greenplum, Hive and delimited text files would be helpful.
3+ years of experience in programming languages like Python, orchestration tools and processes.
Experience in building ETL pipelines using Python pandas.
Extensive experience in data migration, data analysis, data transformations, conversion, interface, large volume data loading (ETL techniques), database modeling, and performance
SQL tuning.
Experience in leveraging database tools to develop DDL scripts, stored procedures, and functions to create and alter database objects.
Hands-on experience with Git version control processes, and other release processes.
Exposure in RDD's with Python/Scala using Spark framework.
Job Description:
CGI is looking for a talented, driven, and experienced Data Engineer with a passion for solving business problems to join our team in Salt Lake City, Utah (this position is located at our client site). At CGI, you will solve challenging business and technical problems serving local, enterprise clients. You'll be part of a team of smart, dedicated people like yourself and make an impact with both internal and client stakeholders. You also can work on cutting edge technologies and cloud native development.
Key Responsibilities:
Partner with architects, engineers, information analysts, business, and technology stakeholders for developing and deploying enterprise grade platforms that enable data-driven solutions.
Demonstrate strong analytical, organizational, and problem-solving skills.
Analyzes and designs technical solutions to address business needs.
Develops, tests, and modifies software to improve efficiency of data platforms and applications.
Identifies, investigates, and proposes solutions to technical problems.
Coordinate with data operations teams to deploy changes into production.
Serve to support Test, QA, and Production environments.