Senior Data Engineer

Mecka•New York, NY

21d

About The Position

Mecka AI is building the data infrastructure layer for robotics and embodied AI. We design and operate global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI and robotics teams. A meaningful portion of our data includes video, sensor streams, and large unstructured datasets used to train and evaluate modern vision-language and robotics models. Making this data reliable, structured, and usable at scale is core to how Mecka operates. The Role We're hiring a Senior Data Engineer to own and evolve Mecka's data infrastructure, pipelines, and internal analytics systems, with a focus on large-scale, unstructured data. This is a high-ownership role. You'll build and maintain pipelines that handle everything from operational metrics to video and multimodal datasets, helping organize, clean, and prepare data for downstream use in analytics, operations, and model training. You'll work closely with operations, engineering, research, and founders to ensure the company can trust and move quickly with its data.

Requirements

6+ years of experience in data engineering or analytics engineering
Proven experience owning production data pipelines end-to-end
Advanced SQL skills and experience working with large datasets
Experience building dashboards and internal analytics tools
Comfortable operating as a senior individual contributor with broad ownership

Nice To Haves

Experience working with video data, sensor data, or multimodal datasets
Experience organizing, cleaning, and pipelining data for ML training or labeling
Familiarity with data preparation workflows for ML training or evaluation
Experience with modern data warehouses (BigQuery, Snowflake, Redshift)
Experience in startups or fast-scaling environments
Worked with messy, real-world, high-volume data
Built pipelines that balance flexibility and correctness
Debugged broken pipelines and late-arriving data
Strong intuition for what data quality actually means in practice
Experience enabling non-technical teams with data

Responsibilities

Design, build, and maintain production-grade data pipelines ingesting structured and unstructured data
Own pipeline reliability, backfills, schema evolution, and performance
Build pipelines that handle large volumes of unstructured data
Support data preparation workflows for vision-language and robotics models
Design data models that support analytics, operations, and research
Organize and clean large datasets, including video and sensor data
Write and optimize complex SQL queries over large datasets
Establish clear metric definitions and data contracts
Build dashboards used by operations, research, and leadership
Develop internal tools and reports to inspect data health, quality, and throughput
Make complex data understandable to non-technical users
Define and implement data quality checks across pipelines
Monitor data freshness, correctness, and completeness
Investigate and resolve data issues across systems
Improve trust in data across the organization
Partner closely with operations, engineering, research, and founders
Translate ambiguous requirements into reliable data systems
Set standards for data engineering practices as the company scales
Mentor and support other engineers as the team grows