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Description:
The Data Engineer will be responsible for creating Data Products in Data Mesh Architecture using the Data Vault Methodology in Snowflake.
They will analyze and create Data Products in SAP Analytics Cloud, finding integration solutions with current implementations.
Collaborate with cross-functional teams to gather requirements, define data schemas, and design scalable data pipelines and workflows.
Mentor and coach junior team members, providing guidance on best practices, code reviews, and technical solutions.
Drive innovation and continuous improvement in data engineering processes and methodologies, staying updated on emerging trends and technologies.
Partner with data architects, data scientists, and business analysts to understand data requirements and deliver solutions meeting business needs.
Ensure data quality, integrity, and security standards are maintained across all data products and pipelines.
Requirements:
Over 3 years of experience in data engineering, with a proven track record of designing and implementing data products in a production environment.
Proficiency in data engineering concepts and technologies such as Data Modeling, ETL Concepts, SQL, Snowflake - Data Vault Methodology, and Data Pipelines.
Experience with SAP Analytics Cloud or willingness to learn and work with this tool.
Familiarity with Data Mesh Architecture framework is highly desirable.
Excellent communication and interpersonal skills to collaborate effectively with stakeholders at all levels.
Strong problem-solving skills, attention to detail, and commitment to delivering high-quality solutions on time and within budget.
Nice-to-have skills:
Talend
SAP Analytics Cloud
CI/CD knowledge
Data Mesh Principles
Tableau
SQL Server, PostgreSQL, SAP
Python
Release Management
Automated Testing / Regression Testing
Benefits:
Opportunity to work for a digital product engineering company that is scaling rapidly.
Dynamic and non-hierarchical work culture.
Remote work option available for employees.
Chance to work with a diverse team of experts across 36 countries.
Continuous learning and growth opportunities in the field of data engineering.
Collaboration with cross-functional teams and exposure to emerging technologies.