Apperture Solutions is looking to lead and architect advanced data engineering initiatives to guide the development of scalable, reliable data solutions that support industrial analytics, business intelligence, and machine learning.
Requirements
- 5+ years of experience in data engineering or a similar role.
- Strong SQL skills and experience with relational databases (e.g., MySQL, PostgreSQL).
- Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP).
- Proficiency in at least one programming language (e.g., Python, Java, Scala).
- Experience with industrial data sources and IoT data such as SCADA/DCS, PLC, or process control.
- Knowledge of data warehousing concepts and technologies (e.g., Redshift, Snowflake).
- Understanding of machine learning concepts and experience with model deployment.
Responsibilities
- Design, implement, and optimize scalable ETL/ELT pipelines and data integration frameworks.
- Lead efforts using analytics platforms (e.g., Seeq) to develop actionable interpretation and visualization of time series data from industrial systems.
- Collaborate with stakeholders to define strategic data initiatives and architecture.
- Architect and manage cloud-based data platforms (AWS, Azure, or GCP) to support analytics and reporting.
- Support deployment and operationalization of machine learning models, advanced analytics solutions, and real-time data processing.
- Ensure data integrity, quality, and security across systems and workflows.
- Enhance CI/CD processes for data solutions with a strong DevOps mindset.
Other
- Provide technical direction and mentorship to junior data engineers and analysts.
- Continuously evaluate emerging technologies to improve data infrastructure and capabilities.
- Support internal customers by developing innovative solutions to meet their data needs.
- Participate effectively in the Scrum process.
- Strong customer service skills.
