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Mid-level data engineer in a metro with a common title and 5+ years, raising candidate competition.
Requires industrial data platforms and domain expertise, limiting cross-industry transferability.
Explicit 5+ years requirement plus mandatory technical skills (SQL, Python, cloud, industrial systems) increases filtering.
Design, deploy, and manage end-to-end industrial data pipelines and digital solutions using Cognite Data Fusion (CDF).
Lead data integration, transformation, contextualization, quality validation, and data model management across diverse industrial and enterprise data sources.
Configure and deploy client digital solutions such as OptiFlow and OptiSite, ensuring reliable functionality and collaboration with stakeholders and software teams.
Bachelor's degree in computer science, IT, Data Engineering, Engineering, or related technical discipline.
5+ years of experience in data engineering, deployment engineering, industrial digitalization, or related fields.
Proven experience with enterprise-scale data integration, data management, and cloud-based deployments (Azure, AWS, or GCP).
Technical expertise in SQL, Python scripting, data quality assessment, and familiarity with industrial systems like PI Systems, SCADA, SAP MES, and Cognite Data Fusion platform.
Experienced in deploying industrial digitalization solutions and client digital products such as OptiFlow and OptiSite.
Strong stakeholder engagement and ability to work across teams including software developers, architects, and client data owners.
Skilled in building scalable, reliable data models and pipelines that support software application development and agile deployment methodologies.