Career Area:

Digital

Job Description:

Responsible and accountable for leading large-scale full-cycle MPP enterprise data warehousing (EDW) projects using on-premise and cloud native data warehousing solutions such as Teradata & Snowflake; Drive development and execution of designing, implementing, and supporting end-to-end automated data processing ETL pipelines using a variety of tools and technologies (e.g. SSIS, SnapLogic, Talend, AWS Glue); Accountable for leading data architecture development for enterprise scale systems in public cloud in AWS, Azure and hybrid eco-systems; Responsible for implementing data lakes, big data transformations, cloud data processing, SQL and NoSQL data modeling; Manage data modeling requirements for structured and non-structured data using various database management technologies such as AWS RDS (SQL Server, PostgreSQL, Aurora), DynamoDB, Timeseries database & Graph Database.

Requires a MS in Computer Science or Information Technology and 7 years of experience in (i) enterprise data architecture; (ii) data management & data modeling for relational databases such as SQL Server and non-relational databases such as AWS DynamoDB (iii) enterprise data warehousing such as Snowflake, data lakes, business intelligence (BI) such as Tableau, data integration such as SSIS, data quality management such as Informatica Data Quality, master data management (MDM) such as Informatica; and (iv) ETL & data pipelines such as AWS Glue. In lieu of the above, Caterpillar would accept a Bachelor’s Degree in Computer Science or Information Technology and 12 years of experience in  (i) enterprise data architecture; (ii) data management & data modeling for relational databases such as SQL Server and non-relational databases such as AWS DynamoDB; (iii) enterprise data warehousing such as Snowflake, data lakes, business intelligence (BI) such as Tableau, data integration such as SSIS, data quality management such as Informatica Data Quality, master data management (MDM) such as Informatica; and (iv) ETL & data pipelines such as AWS Glue.