Data Engineer III-6348

itD Tech•San Jose, CA

3d•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. The role replaces manual operational reporting with automated, reliable systems and requires experience in dimensional modeling, production pipeline ownership, and distributed SQL and Python. The position is remote in the United States, full-time at 40 hours per week, for an initial 12-month duration with a strong possibility of extension or conversion. The start date is ASAP. The pay rate is $48.60 per hour, depending on experience. Only direct W2 candidates are being considered, and sponsorship is not available. The Data Engineer will work with operational teams across two U.S. sites to develop trustworthy reporting infrastructure and metrics. The role includes defining consistent metric standards, owning pipeline accuracy and freshness, building operational dashboards and views, and automating recurring reporting workflows. The engineer will also participate in itD practice activities, including community meetings, thought leadership, case studies, learning materials, networking, and career development. itD describes itself as a consulting and software development company that blends diversity, innovation, and integrity, with a non-hierarchical structure. It is a woman- and minority-led firm and offers a global community, opportunities to work with Fortune 500 companies and high-performance teams, and opportunities to contribute to causes that matter. itD is committed to equal opportunity and reasonable accommodation for applicants with disabilities.

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 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 backfill 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 ability to partner with non-technical operational and senior stakeholders, up to director level, in an ambiguous environment.
Must be a direct W2 candidate; sponsorship is not available.

Nice To Haves

Experience in a physical operations, manufacturing, logistics, or fleet environment, including uptime, utilization, yield, throughput, or downtime attribution.
Working knowledge of TypeScript/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 covering collection volume, operator efficiency, data quality, and equipment uptime across multiple collection methods.
Build daily and cumulative table layers that allow recurring reporting to be generated automatically.
Define and document canonical metric definitions and align teams on consistent terminology across dashboards, internal apps, and leadership reporting.
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 metric definitions or upstream sources change.
Build and own dashboards and internal reporting views, including live fleet-status views and automatically generated daily operational briefs.
Develop lightweight input interfaces that combine 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.
Collaborate with the itD practice team on industry thought leadership.
Complete client case studies and learning materials, including blogs and media material.
Build materials to contribute to the Digital Transformation practice.
Attend internal itD networking events, both in person and virtual.
Work with leadership on career fast-track opportunities.