Data Engineer

Base pay range

$/yr - $/yr

Direct message the job poster from RSM Solutions, Inc.

Data Integration Engineer – Onsite in Irvine, California.

I am Tom Welke, Partner & VP at RSM Solutions, Inc. I have been recruiting technical talent for more than 23 years and have been in the tech space since the 1990s. I write my own job descriptions without relying on AI or bots. I focus on clear, realistic expectations. Technical fit is the highest priority; social fit is also important.

The hiring manager is a longtime friend who values continuous learning – a key culture of this environment.

This role requires U.S. Citizenship or Green Card Holder status only. All other visa categories are not eligible.

• Design and implement batch and streaming pipelines in Apache Spark running on Kubernetes and Kubeflow Pipelines to hydrate feature stores and training datasets.
• Build high throughput ETL/ELT jobs with SSIS, SSAS, and T SQL against MS SQL Server, applying Data Vault style modeling patterns for auditability.
• Integrate source control, build, and release automation using Git Hub Actions and Azure Dev Ops for every pipeline component.
• Instrument pipelines with Prometheus exporters and visualize SLA, latency, and error budget metrics to enable proactive alerting.
• Create automated data quality and schema drift checks; surface anomalies to support a rapid incident response process.
• Use MLflow Tracking and Model Registry to version artifacts, parameters, and metrics for reproducible experiments and safe rollbacks.
• Work with data scientists to automate model retraining and deployment triggers within Kubeflow based on data freshness or concept drift signals.
• Develop Power Shell and .NET utilities to orchestrate job dependencies, manage secrets, and publish telemetry to Azure Monitor.
• Optimize Spark and SQL workloads through indexing, partitioning, and cluster sizing strategies, benchmarking performance in CI pipelines.
• Document lineage, ownership, and retention policies; ensure pipelines con‑form to PCI/SOX and internal data governance standards.

• At least 6 years of experience building data pipelines in Spark or equivalent.
• At least 2 years deploying workloads on Kubernetes/Kubeflow.
• At least 2 years of experience with MLflow or similar experiment‑tracking tools.
• At least 6 years of experience in T‑SQL, Python/Scala for Spark.
• At least 6 years of Power Shell/.NET scripting.
• At least 6 years of experience with Git Hub, Azure Dev Ops, Prometheus, Grafana, SSIS/SSAS.
• Certifications such as Kubernetes CKA/CKAD, Azure Data Engineer (DP‑203), or MLOps‑focused certifications (e.g., Kubeflow or MLflow) are desirable.
• Experience mentoring engineers on best practices in containerized data engineering and MLOps.

Mid–Senior level

Full‑time

Information Technology – Manufacturing and Retail Apparel & Fashion

• Medical insurance
• Vision insurance
• 401(k)

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