Data Architect

3 weeks ago

San Francisco, California, United States Plato Systems Full time

Plato Systems is a pioneer in the use of spatial AI to enhance capacity, productivity, and safety across physical operations, starting with manufacturing.

As a spin-off from Stanford and backed by NEA in 2019, the company has developed an Operations Digital Twin and AI copilot powered by proprietary hardware that leverages machine perception and sensor fusion on the edge to digitize patterns of activity.

The platform's capabilities have been harnessed by advanced manufacturing companies to rapidly and at scale root cause complicated systemic operational issues, thereby propelling Kaizen and compliance tracking into the age of AI.

Deployed globally across multinational electronics manufacturers, semiconductor fabs, and EMS companies, Plato Systems continues to push the boundaries of innovation.

We are seeking a Senior Data Engineer with over 7 years of relevant experience to join our growing team.

The ideal candidate will have a deep grasp of designing, developing, and maintaining multiple ETL pipelines, be confident working with time-series data, and possess prior experience with business analyst or business intelligence functions.


Key Responsibilities & Qualifications:

ETL Pipeline Design and Development:

Collaborate with our Head of Product to design and maintain complex ETL data pipelines using SQL and PySpark, ensuring data quality.

Familiarity with Databricks is highly preferred.


Time-Series Data Processing:

Prior experience in designing and implementing production pipelines for normalizing, aggregating, aligning, correlating, and processing time-series data from sensors, machines, and processes, as well as orchestrating and monitoring.


Production Data Product Experience:

Demonstrated ability to work on the production of data products, including handling data quality issues, orchestration, automation, and testing.


Coding Skills:

Proficiency in Python, SQL, and Java or other backend languages, with familiarity with cloud platforms like AWS, GCP, or Azure being a significant plus.


Communication Requirements:

Effective communication skills, both verbal and written, to clearly explain complex data concepts to non-technical team members and stakeholders.


Team Collaboration:

Proven experience working effectively in cross-functional teams, demonstrating a collaborative mindset.



Preferred Qualifications:

Domain Engagement:

Demonstrated prior experience understanding business requirements and domain to create data products that address customer needs.

Success in this role hinges on grasping the nuances and intricacies of our domain to offer relevant and impactful data solutions.


Autonomy & Attention to Detail:

Derived tables that feed dashboards and analytics are only useful if they contain clean, high-quality data.

This requires good judgment to find the right balance of unit tests, integration tests, regression tests, and monitoring/alerting to ensure data flow and its quality.


BI, Data Visualization & Reporting:

Prior experience creating and maintaining automated reporting, dashboards, and consistent analysis to bolster data-driven decisions.


Versatility of Prior Work:

Experience working in different industries or domains, as well as different stages (early stage build-out to mature pipelines and processes), showing flexibility and ability to adapt to new types of data and/or business domains.

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