Data Engineer

We are seeking a Data Engineer to support the design and development of scalable data platforms within a large-scale manufacturing and enterprise data environment. This role focuses on building and optimizing data pipelines, transforming raw data into reliable datasets, and enabling the foundational architecture for analytics, reporting, and downstream AI-driven use cases. The ideal candidate will be highly technically proficient with strong experience in data engineering, cloud platforms, and distributed data processing, while also possessing the communication skills to bridge the gap between diverse application teams. This role will play a key part in supporting centralized enterprise data hubs and foundational AI proof-of-concept initiatives within a manufacturing setting., * Design, build, and maintain scalable data pipelines for ingesting and processing data from enterprise systems, local databases, and operational platforms.

• Develop and optimize ETL / ELT workflows for large-scale data processing.
• Act as a technical bridge between various application teams to ensure seamless data integration and alignment on AI data requirements.
• Support both batch and real-time data systems across manufacturing environments.
• Integrate data from operational systems and Industrial IoT platforms into centralized enterprise data hubs.
• Ensure data quality, integrity, observability, and performance optimization.
• Collaborate with software engineers, AI engineers, and business stakeholders to define data requirements.
• Support data modelling and data architecture for analytics, reporting, and AI consumption.
• Enable data availability for business intelligence and downstream AI applications.
• Support proof-of-concept execution for foundational AI initiatives within a manufacturing environment., * 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.

• Strong experience in SQL and Python.
• Experience building data pipelines and ETL / ELT processes.
• Strong understanding of data modelling and data warehousing concepts.
• Experience with cloud platforms (AWS preferred).
• Experience working with large-scale or distributed data systems.
• Proven ability to act as a technical liaison between cross-functional application teams.
• Strong problem-solving and production support mindset.
• Ability to travel up to 10% domestically or internationally, within North America, during peak times.

Preferred Skills:

• Experience with big data and streaming technologies (Spark, Kafka, NiFi).
• Exposure to real-time or event-driven data systems.
• Familiarity with orchestration tools (Airflow or similar).
• Exposure to AI/ML data pipelines or supporting machine learning workflows.
• Experience with Databricks, Snowflake, or Redshift.

Nice to Have:

• Experience in manufacturing, automotive, industrial, or enterprise data environments.
• Exposure to IoT or telemetry data systems.

• 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.

At OP, we help you harness the power of technology for maximum impact. A technology consulting and solutions company, we offer advisory and managed services, innovative platforms, and staffing solutions across a wide range of fields including AI, cyber security, enterprise architecture, and beyond. For nearly two decades, we’ve been challenging the status quo of the consulting industry, serving up fresh, ingenious thinking through a radically lean structure. Together, this strategy delivers unprecedented performance at an unparalleled pace for faster results that propel your business forward.