Data Engineer

Data Engineer

Salary: $67,500-$90,000

Benefits include:

• Paid vacation, holiday and sick time
• Medical, dental, and vision insurance options
• 401(k)/profit sharing

Skills

Data/ETL Testing: 5 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 5 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.

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