Data Engineer
Overview:
Considering applying for this job Do not delay, scroll down and make your application as soon as possible to avoid missing out. As a Data Engineer in a contract-to-permanent role, you will design and maintain scalable data pipelines connecting enterprise and operational sources to analytics platforms. You will build curated data models and support BI and data-driven decision making across finance, supply chain, operations, and analytics teams. The role spans IT and OT integration, enforcing data quality, security, and governance while enabling reliable data delivery. You will collaborate with BI, IT, and plant teams to improve observability, performance, and deployment reliability, shaping data solutions for the organization.
Responsibilities:
- Design, build, and maintain large-scale data pipelines from source systems to analytics layers
- Develop curated and semantic data models for BI and downstream applications
- Integrate manufacturing and OT data sources with approved methods while coordinating with plant teams
- Establish data quality standards with validation, automated tests, and monitoring
- Implement observability practices including lineage tracking and alerting
- Apply security and governance controls (access, secrets, data classification, retention)
- Automate deployments with Git-based CI/CD for reliable releases
- Tune performance and storage for speed and cost balance
- Collaborate with BI, data, and IT stakeholders to define data contracts and transfer knowledge
Key requirements:
- Experience in designing and building data pipelines for analytics and reporting
- Knowledge of data modeling for analytics platforms
- Experience with OT/IT data xaygatp integration and plant/controls collaboration
- Data quality, validation, monitoring, and lineage
- Data security and governance practicesCI/CD and git-based deployment workflows
- Performance tuning and scalable storage strategies
- Stakeholder collaboration for data contracts and documentation
- Cross-functional collaboration
- CommunicationProblem-solving orientation
- Data pipeline design and implementation
- Semantic data modeling for BIOT/IT data integration