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 Work

In this role, you will:

• Build data pipelines: Create, maintain, and optimize workloads from development to production for specific use cases
• Use innovative and modern tools, techniques and architectures listed below to drive automation of most-common, repeatable data preparation and integration tasks with goal of minimizing reducing defects and improving productivity
• Develop and enforce data integration and data quality standards across all development initiatives according to the organization’s Enterprise information services policies as well as best practices
• Assist in renovating our data management infrastructure with quality of data preparation, integration and AI-enabled metadata management tools and techniques
• Track data consumption patterns most used and valued to our customers by performing intelligent sampling and monitoring
• Triage data issues, analyzing end to end data pipelines and in working with business users in troubleshooting/resolving data pipeline issues
• Execute and oversee the analysis and remediation of root causes, including deficiencies in technology, process, or resource capabilities
• Work in an Agile/DevSecOps pod model alongside solution leads, data modelers, analysts, business partners and other developers in delivery of data

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