Senior Data Engineer Lead — Cloud, AI & RAG Pipelines

Pace Industries, LLC; Northern (KY); Hybrid; USD 166,000 - 243,000; Full time

Job summary

Rackspace is seeking a Data Engineer V to lead the data engineering pod, shaping the technical direction for EDW pipelines and AI/RAG data infrastructure. Translate stakeholder needs into a prioritized roadmap while mentoring engineers and owning operational accountability for the team's pipelines.

You will set standards for SQL data modeling, batch/streaming architectures (Spark, Airflow, Databricks, Snowflake) and CI/CD, guiding AI/RAG data pipelines, embedding strategies, and vector-store

Qualifications

• Bachelor's in CS or related field or equivalent hands-on experience.
• 8–12 years of technology experience with data-centric leadership.
• 6–8 years architecting data solutions on a cloud platform.
• 2+ years leading engineers or technical workstreams.

Responsibilities

• Lead and mentor a pod of engineers, prioritizing workload and on-time delivery.
• Define and enforce source management, version-control, and QA standards including AI code contributions.
• Define and track metrics; own SLA/SLO tracking for pipelines and back-to-green plans.
• Track and report KPIs (uptime, MTTR, data quality) to leadership.
• Own root-cause analysis for complex pipeline/data-quality issues.
• Translate stakeholder needs into the team roadmap (pipelines, data products, AI/RAG).
• Contribute cloud/AI budget input for usage and optimization.
• Produce documentation, SOPs, and escalation paths.
• Participate in on-call rotation and escalation ownership.

Skills

SQL

Data modeling

Semantic-layer design

Spark

Airflow

CI/CD

AI/RAG pipelines

Stakeholder communication

Education

Bachelor's in CS or related field

Equivalent hands-on experience

Tools

Spark

Airflow

Databricks

Snowflake

Job description

Rackspace is seeking a Data Engineer V to lead the data engineering pod, shaping the technical direction for EDW pipelines and AI/RAG data infrastructure. Translate stakeholder needs into a prioritized roadmap while mentoring engineers and owning operational accountability for the team's pipelines.

You will set standards for SQL data modeling, batch/streaming architectures (Spark, Airflow, Databricks, Snowflake) and CI/CD, guiding AI/RAG data pipelines, embedding strategies, and vector-store