Senior Data Engineer: Autonomous Plant Data & ML Pipelines

Talentify; Houston (TX); On-site; USD 140,000 - 180,000; Full time

Job summary

Mariana Minerals is seeking a Senior Data Engineer to own end-to-end data domains, designing pipelines, schemas, and contracts across plant data. You will work on the PlantOS platform for autonomous mineral refining, collaborating with ML engineers to feed production models with trustworthy data.

The role requires building robust, scalable data architectures in a cloud environment, mentoring engineers, and shaping data contracts across teams to enable model-driven operations.

Qualifications

• 4-8+ years in data engineering or a closely related role.
• Strong Python and SQL, with deep experience designing database and warehouse schemas, including time-series and/or analytical data.
• Proven experience building reliable, orchestrated data pipelines and operating them in the cloud with containers and CI/CD.
• Experience with data quality, observability, and lineage, and comfort with messy real‑world sources—drifting sensors, malformed exports, and the quirks of industrial systems.
• A self‑starter comfortable in high‑ambiguity environments, working directly with process engineers, ML engineers, and operations teams.
• Bonus: experience feeding data to ML systems—training datasets, feature pipelines, model monitoring—or working with industrial, sensor, or historian data.

Responsibilities

• Work across domains—for example, all plant sensor and historian data, or all lab and analytical results—including schema design, orchestration, reliability, and the contract it exposes to everyone downstream.
• Design and evolve our fleet of pipelines that pull from messy industrial sources—sensors, lab systems, historians, imagery, and more—into our databases and warehouse.
• Model time‑series and analytical plant data for both human analysis and machine learning training, validation, and monitoring; own data quality, observability, and lineage in your domain.
• Build the data architecture that feeds production ML—the training and monitoring layer—in partnership with the ML engineers who own the model-specific semantics.
• Mentor earlier-career engineers and define the data contracts other teams build against.
• Work the boundary with machine learning deliberately: you own the platform and the interface it exposes; ML engineers own the features and models built on top of it. The training and monitoring layer is shared ground you design together.

Skills

Python

SQL

Data modeling

Time-series data

Data warehousing

CI/CD

Docker

Kubernetes

Tools

Docker

CI/CD

Kubernetes

Job description

Mariana Minerals is seeking a Senior Data Engineer to own end-to-end data domains, designing pipelines, schemas, and contracts across plant data. You will work on the PlantOS platform for autonomous mineral refining, collaborating with ML engineers to feed production models with trustworthy data.

The role requires building robust, scalable data architectures in a cloud environment, mentoring engineers, and shaping data contracts across teams to enable model-driven operations.