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Data Engineer

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Data Engineer

Skills

Data/ETL Testing: 10-12 years of experience in data and ETL testing.

MDM Expertise: Proficiency in Master Data Management, specifically with Stibo.

Data Processes: Skilled in data analysis, migration, validation, cleansing, verification, and handling data import/export.

Tool Proficiency: Experience with other MDM/ETL tools and cloud-based MDM testing.

Data Integrity: Ability to identify and address data integrity compliance gaps within quality systems.

ETL Knowledge: Comprehensive understanding of ETL processes from various source systems to data marts and loads.

Analytical Abilities: Capable of interpreting and testing data from diverse sources to support integration and reporting needs.

Development/Testing: Proficient in developing and testing ETL solutions on cloud and on-prem platforms like Ab Initio, AWS Glue, Informatica, and Alteryx.

Pipeline Construction: Expertise in building data flow CI/CD pipelines in GitLab.

DevOps/DataOps: Experience in the DevOps and DataOps space.

Data Modeling: At least 3 years of experience in data modeling principles and data integration techniques.

Quality Management: At least 6 years of experience in data quality management and governance within an MDM environment.

Communication: Strong communication and collaboration skills to effectively work with functional teams and stakeholders.

Responsibilities

Data Integration: Design, develop, and maintain data integration processes ensuring seamless data flow across systems.

Stibo MDM: Implement and configure Stibo MDM solutions to fulfill business requirements.

Quality Assurance: Monitor, measure, and improve the quality of master data metrics.

Testing: Conduct tests to ensure data accuracy, consistency, and reliability.

Collaboration: Work closely with business units to confirm data quality policies and governance attributes.

Documentation: Create and maintain documentation for data processes and systems.

Compliance: Identify and address data integrity compliance gaps across quality systems.

Data Analysis: Analyze data from various sources to support integration and reporting needs.

Development/Testing: Develop and test ETL solutions on cloud and on-prem platforms.

CI/CD Pipelines: Build and manage data flow CI/CD pipelines in GitLab.

Team Interaction: Collaborate with key business functions and stakeholders to ensure data quality and governance practices are adhered to.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
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