Data Engineer
Role details
Job location
Tech stack
Job description
- Design, build, and maintain scalable data pipelines for ingesting and processing data from multiple sources.
- Develop and optimize ETL/ELT workflows for large-scale data processing.
- Work with both batch and real-time data systems.
- Ensure data quality, integrity, and performance optimization.
- Collaborate with software engineers, AI engineers, and business stakeholders to define data requirements.
- Support data modeling and data architecture for analytics and reporting.
- Enable data availability for business intelligence and downstream data-driven applications., * Participate in OP monthly team meetings and participate in team-building efforts.
- Contribute to OP technical discussions, peer reviews, etc.
- Contribute content and collaborate via the OP-Wiki/Knowledge Base.
- Provide status reports to OP Account Management as requested.
Requirements
We are on the lookout for a Data Engineer to support the design and development of scalable data platforms within a manufacturing and enterprise data environment. This role focuses on building and optimizing data pipelines, transforming raw data into reliable datasets, and enabling analytics, reporting, and downstream data-driven use cases. The ideal candidate will have strong experience in data engineering, cloud platforms, and distributed data processing, with the ability to work across both batch and real-time data systems., * Strong experience in SQL and Python.
- Experience building data pipelines and ETL/ELT processes.
- Understanding of data modeling and data warehousing concepts.
- Experience with cloud platforms (AWS).
- Experience working with large-scale or distributed data systems.
Preferred Skills:
- Experience with big data and streaming technologies (Spark, Kafka, NiFi).
- Exposure to real-time or event-driven data systems.
- Familiarity with data orchestration tools (Airflow or similar).
- Exposure to operational or time-series data environments.
- Exposure to AI/ML data pipelines or supporting machine learning workflows is a plus.
Nice to Have:
- Experience in manufacturing, industrial, or enterprise data environments.
- Exposure to IoT data systems.
Benefits & conditions
- 401(k).
- Dental Insurance.
- Health insurance.
- Vision insurance.
- We are an equal-opportunity employer and value diversity, equality, inclusion, and respect for people.
- The salary will be determined based on several factors, including, but not limited to, location, relevant education, qualifications, experience, technical skills, and business needs.