Data Engineer III-6348

itD Tech•San Jose, CA

1d•Remote

About The Position

itD is seeking a Data Engineer to design, build, and own data models, pipelines, and reporting for a large-scale robot teleoperation and wearable data collection operation at a leading global technology company. The role will replace manual operational reporting with automated, trustworthy systems. The successful candidate will have experience in dimensional modeling, production pipeline ownership, and distributed SQL and Python, and will deliver reliable reporting infrastructure and metrics trusted by leadership. The position is remote within the U.S. It is a 12-month, full-time engagement at 40 hours per week, starting ASAP, with a strong possibility of extension or conversion. The pay rate is $48.60 per hour, depending on experience. Direct W2 candidates only; sponsorship is not available. The engineer will partner with site leads, operators, program managers, and engineers across two U.S. sites. The work includes creating consistent metric definitions, building and maintaining production pipelines and automated data-quality controls, owning reporting dashboards and operational workflows, and supporting daily and weekly operating cadences as well as leadership analysis. The role also includes internal itD practice responsibilities, such as attending practice community meetings and networking events, contributing to thought leadership and Digital Transformation materials, completing client case studies and learning materials, and working with leadership on career fast-track opportunities.

Requirements

Bachelor of Science in Computer Science, Data Engineering, or a related technical field.
At least 5 years of professional data engineering experience.
Strong Python and SQL skills, including query performance work on very large partitioned tables in a distributed query engine such as Presto, Trino, Spark SQL, BigQuery, Snowflake, or similar.
Experience with dimensional modeling and data warehouse design, including star schemas, slowly changing dimensions, and incremental and cumulative table patterns.
Pipeline orchestration experience with scheduled workflows, dependency management, retries, and backfills using Airflow, Dagster, or an equivalent tool.
Demonstrated ownership of a production data pipeline, with accountability for correctness, freshness, and backfill.
Experience defining and documenting metrics as an organizational source of truth for a non-technical audience.
Experience building or owning dashboards in a BI tool such as Tableau, Looker, Power BI, or equivalent.
Comfort working in a large shared codebase with code review and CI.
Strong written communication skills and the ability to partner with non-technical operational and senior stakeholders up to director level in an ambiguous environment.

Nice To Haves

Experience in physical operations, manufacturing, logistics, or a fleet environment, including uptime, utilization, yield, throughput, or downtime attribution.
Working knowledge of TypeScript and React sufficient to make contained changes to an existing internal web app.
Experience with robotics, sensor, or time-series data, such as ROS bags or MCAP.
Experience with multimodal or unstructured data at scale, such as video or sensor streams, and the metadata layer built over it.
Familiarity with large-scale object storage systems.
Prior experience supporting a data-collection, annotation, or labeling operations team.
Startup or smaller-company background with exposure to back-end systems and cross-team work.

Responsibilities

Design and own dimensional data models for collection volume, operator efficiency, data quality, and equipment uptime across multiple collection methods.
Build daily and cumulative table layers that enable recurring reporting to be derived automatically.
Define and document canonical metric definitions and drive alignment when teams disagree about metric meaning.
Build and extend batch data pipelines from operational source systems through daily snapshots to cumulative dimension tables.
Own the correctness, freshness, and backfill of reported metrics, and resolve discrepancies against source data.
Build automated data-quality checks, anomaly detection, and freshness SLAs.
Own backfill and restatement strategies, including communicating restatements to stakeholders when definitions or upstream sources change.
Build and own dashboards and internal reporting views, including live fleet-status views and automatically generated daily operational briefs.
Build lightweight input interfaces that pair human context with automated metrics.
Automate recurring operational workflows, including daily production reporting, equipment status and maintenance tracking, and weekly metrics-review assembly.
Partner with site leads, operators, program managers, and engineers across two U.S. sites to turn operational questions into durable data models.
Support daily and weekly operating cadences and deliver defensible ad-hoc analysis for leadership.
Attend regular internal practice community meetings and internal itD networking events, both in person and virtually.
Collaborate with the itD practice team on industry thought leadership and contribute material to the Digital Transformation practice.
Complete client case studies and learning materials, including blogs and media material.
Work with leadership on career fast-track opportunities.