Sr. Data Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work

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Application

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Deadline

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About this role

Sr. Data Engineer Ann Arbor, MI, Ann Arbor, Michigan, United States, Houston, TX, San Francisco HQ About Mariana Minerals Mariana Minerals is a software-first, vertically integrated minerals company on a mission to supply the critical minerals powering modern energy, AI, and defense technologies. We're reimagining the minerals supply chain by combining deep industry expertise with advanced software, automation, and data-driven decision-making. The Role Mariana Minerals is building the critical minerals supply chain from the ground up-and we're looking for a Senior Data Engineer to help make it autonomous. We're not a software company selling tools to mining operators. We are a mining company that builds software. Mariana designs, builds, commissions, and operates our own mines and refineries. We develop proprietary chemical processes and run them at lab, pilot, and commercial scale. Today, we're producing battery-grade lithium salts from real oil and gas wastewater in our facilities. Our first commercial-scale lithium production facility, Lithium One, is targeting initial production in Q1 of 2027. As a Senior Data Engineer at Mariana, you'll own a data domain end-to-end-designing the pipelines, schemas, and contracts that make a whole class of plant data trustworthy and queryable. The systems you build are the foundation every model and every operational decision depends on. The Tech This is some of the most interesting applied data work happening today. Our internal platform, PlantOS, uses the same reinforcement learning toolkits that power self-driving vehicles and humanoid robots-but applied to autonomous, short-interval control of mineral refining circuits. None of it works

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