Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 brand plus remote, generalist data-engineer title and broad skill requirements increase competition.
Core data engineering skills are transferable, but ERP/SAP and Azure specifics increase industry sensitivity.
No numeric years but many mandatory technologies and domain tools imply medium strictness.
Develop and maintain structured data sets and data models to support business analytics including management, operational, predictive, and data science requirements.
Design, develop, and support scalable ETL packages and routines to extract and transform data from various business source systems including ERP platforms like SAP, Oracle, MS Dynamics.
Participate in testing, validation, data migration, and provide analysis and documentation to ensure accurate and efficient data transformations and system changes.
Bachelor's degree or equivalent in computer science, software engineering, IT, or related field.
Moderate level experience in data engineering and data mining within fast-paced environments, including experience with big data tools (Hadoop, Cassandra, Storm) and scripting languages (Perl, Bash, Shell, Python).
Experience with database systems (SAP, SQL, MySQL, Microsoft SQL) and data analytics tools like Microsoft Azure Data Factory, SQL Analysis Server, SAP Data Services.
Workplace type: Remote Working. Work Experience Required: Moderate level experience; no exact years specified.
Experienced in building modern scalable data analytics solutions handling multi-terabyte datasets, emphasizing secure and highly available system architectures.
Skilled in automation and scripting with proven implementation successes, comfortable working with multiple programming and scripting languages.
Strong understanding of data architecture, object and data modeling techniques, and capable of supporting requirements scoping and prioritization for data-related projects.