Data Engineer, Senior

Your Role

The Data Engineering development team is responsible for design, development, test and deployment of large enterprise data warehouse/BI data solutions using both on-prem and cloud technologies. The Data Engineer, Senior will report to the Manager, Data Engineering Development. In this role you will be responsible for design, development, and implementation of data integration, data warehouse and data mart (ELT/ETL) solutions using on-prem as well as Cloud technologies.

Your Knowledge and Experience

• Requires a bachelor's degree or equivalent experience
• Requires at least 5 years of prior relevant experience
• Hands on experience with programming languages including SQL, PL/SQL on cloud data platforms like Snowflake, Oracle, SQL Server and Netezza
• Strong technical understanding of data modeling (data vault 2.0), data mining, master data management, data integration, data architecture, data virtualization, data warehousing and data quality techniques with hands on experience using data management technologies like Informatica PowerCenter/IICS, Collibra, Master Data Management, DBT Cloud, Denodo and Golden Gate.
• Working knowledge of Git repositories (bitbucket, GitHub), CI/CD (Jenkins, Azure DevOps)and software development tools, including incident tracking, version control, release management, subversion change management(Atlassian toolset - Jira/Confluence), testing tools and systems and scheduling software (Tidal, Control-m)
• Experience working with popular data discovery, analytics and BI software tools like Tableau, Qlik, PowerBI and others for semantic-layer-based data discovery
• Experienced in popular open-source and commercial data science platforms such as Python, R, KNIME, Alteryx, others is a strong plus but not required/compulsory
• Basic experience in working with data governance and data security and specifically information stewards and privacy and security officers in moving data pipelines into production with appropriate data quality, governance and security standards and certification
• Adept in agile methodologies and capable of applying DevOps and increasingly Data Operations principles to data pipelines to improve the communication, integration, reuse and automation of data flows between data managers and consumers across an organization