Lead Data Engineer - Multi-Cloud (GCP/Azure Databricks)

Burns & McDonnell; Kansas City (MO); On-site; USD 140,000 - 200,000; Full time

Job summary

Burns & McDonnell is seeking a senior data engineer who combines an architecture mindset with hands-on execution to design scalable data systems. You will own end-to-end pipelines across Google Cloud and Azure Databricks, mentor engineers, and bridge business needs with robust data solutions.

You will lead technical direction, establish data engineering standards, and collaborate with product managers and analysts to deliver secure, reliable data platforms across multi-cloud environments.

Qualifications

• Bachelor’s degree in Computer Science, MIS, Engineering or related field.
• 8+ years in data engineering or related field.
• Strong programming and coding principles.
• Excellent communication and collaboration skills.
• Experience with multi-cloud data platforms is a plus.
• Hands-on production experience with Google Cloud and Azure Databricks.

Responsibilities

• Architect, build, and ship scalable data pipelines to production.
• Lead end-to-end data product lifecycles and define SLAs.
• Provide technical leadership and mentorship to engineers.
• Set standards for CI/CD, testing, and documentation.
• Drive multi-cloud data movement, security, and cost governance.
• Collaborate with product managers and stakeholders to align roadmaps.
• Define data schemas and ensure data quality baselines.
• Monitor pipelines and troubleshoot production issues.
• Evaluate new tech, including generative AI integrations.

Skills

Programming languages

Web development

Communication

Analytical thinking

Team collaboration

Documentation

Certifications

Education

Bachelor degree in CS/MIS/Engineering

Tools

Google Cloud Platform

BigQuery

Dataflow

Azure Databricks

Delta Lake

Unity Catalog

Dataform

dbt

Airflow

Kafka

Pub/Sub

Confluent

Job description

Burns & McDonnell is seeking a senior data engineer who combines an architecture mindset with hands-on execution to design scalable data systems. You will own end-to-end pipelines across Google Cloud and Azure Databricks, mentor engineers, and bridge business needs with robust data solutions.

You will lead technical direction, establish data engineering standards, and collaborate with product managers and analysts to deliver secure, reliable data platforms across multi-cloud environments.