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Lead Data Engineer - Google Cloud & Azure Databricks (Kansas City)

Burns & McDonnell

Kansas City, MOFull-timeSeen 1 day agoSeen in employer's feed 1 day ago

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At a glance

Compensation
No compensation found
Location
Kansas City, MO
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Requirements

Credentials this posting asks for.

Applicable CertificationsBachelor's degree

Job overview

Burns & McDonnell seeks a senior lead data engineer to own data pipelines across Google Cloud and Azure Databricks, from architecture through production. The role sets technical direction for enterprise data products, mentors engineers, and connects business stakeholders with engineering teams. It focuses on scalable, secure data solutions and multi-cloud platform standards.

Skills & qualifications

RequiredNice to have

Skills

Programming LanguagesCoding PrinciplesWeb Development FrameworkAttention to DetailFacilitationTeam BuildingCollaborationOrganizationProblem-SolvingVerbal CommunicationWritten CommunicationQuantitative Problem-SolvingCritical ThinkingMicrosoft Office SuiteGoogle CloudBigQueryDataflowAzure DatabricksApache SparkPySparkDelta LakeUnity CatalogMulti-Cloud Data PlatformsConfluent KafkaGoogle Pub/SubAirflowSQLDataformDbtOracleSQL ServerPostgreSQLPythonJavaData Product DeliveryData QualityCross-Functional CollaborationBusiness Requirements TranslationEngineering Team LeadershipAgentic Tooling

Qualifications

Bachelor's in Computer Science, MIS, Engineering or Related8 Years ExperienceApplicable Certifications10+ Years Data Engineering, Warehousing or Architecture5+ Years Technical Leadership, Mentoring or ConsultingGoogle Cloud Professional Data Engineer or Cloud Architect CertificationDatabricks Certified Data Engineer Professional or Azure Data CertificationsPower BI Certifications

Full job description

Description

Overview:

We're looking for a senior engineer who combines an architecture mindset with deep hands-on experience — someone who can design scalable systems and personally build and ship them into production. As our lead data engineer, you will own pipelines end-to-end across Google Cloud and Azure Databricks, from whiteboard to running code, while setting the technical direction for our enterprise data products, mentoring the team, and serving as the bridge between business stakeholders and engineering to turn strategic goals into robust, secure data solutions.

Responsibilities:

  • Architect, build, and ship scalable batch and streaming data pipelines into production using BigQuery Dataform, Google Cloud Dataflow, Confluent Kafka, and Pub/Sub.

  • Design and build data pipelines on Azure Databricks using Apache Spark, Delta Lake, and Unity Catalog, keeping engineering patterns consistent with our Google Cloud platform.

  • Manage the end-to-end data product lifecycle, serving as the technical owner for critical data assets and establishing clear service level objectives.

  • Provide technical leadership and mentorship to junior and senior engineers, conducting code reviews and fostering a culture of technical excellence.

  • Lead the engineering team across Google Cloud and Azure Databricks environments, setting multi-cloud architecture standards for data movement, interoperability, security, and cost management.

  • Partner with product managers, business analysts, and leadership to define data product requirements, align roadmaps, and manage engineering delivery schedules.

  • Define, document, and enforce data engineering standards, including CI/CD practices, robust testing frameworks, and comprehensive technical documentation.

  • Own the monitoring, cost optimization, and troubleshooting of production pipelines to maintain reliable business operations.

  • Evaluate emerging technologies, particularly generative AI integrations and advanced governance tools, to continuously improve data platform capabilities.

Qualifications

Required:

  • Bachelor Degree in Computer Science, Management Information Systems, Engineering or related field and 8 years Required

  • Expert knowledge in programming languages and coding principles and procedures.

  • Expert in web development framework.

  • Strong attention to detail, facilitation, team building, collaboration, organization, and problem-solving skills.

  • Excellent verbal and written communication skills.

  • Ability to work methodically and analytically in a quantitative problem-solving environment.

  • Demonstrated critical thinking skills.

  • Expert in Microsoft Office Suite (Word, Excel, and PPT).

  • Strong attention to detail, facilitation, team building and collaboration.

  • Ability to obtain applicable certifications.

Strongly Preferred:

  • Ten or more years of experience in data engineering, data warehousing, or data architecture, with at least five years in a technical leadership, mentoring, or consulting role.

  • Deep technical expertise with Google Cloud, BigQuery, Dataflow, and related cloud data services.

  • Hands-on production experience with Azure Databricks, including Apache Spark (PySpark), Delta Lake, and Unity Catalog.

  • Proven experience architecting and leading delivery on multi-cloud data platforms, ideally spanning Google Cloud and Azure.

  • Production experience designing and deploying real-time streaming architectures using messaging platforms like Confluent Kafka or Google Pub/Sub.

  • Strong expertise in workflow orchestration using scheduling tools like Airflow.

  • Advanced SQL skills and extensive experience with transformation frameworks like Dataform or dbt.

  • Production experience with at least one transactional database, such as Oracle, SQL Server, or PostgreSQL.

  • Strong hands-on coding skills in Python or Java, with a track record of personally shipping production-grade data pipelines.

  • Demonstrated experience managing data product delivery, defining schemas, and establishing data quality baselines.

  • Strong communication skills with a proven track record of collaborating with cross-functional stakeholders and translating business needs into technical specifications.

  • Strong problem-solving abilities and experience leading engineering teams in fast-paced environments.

  • Experience coding with agentic tooling as part of generative AI workflows.

  • Direct experience implementing data mesh principles, managing data products, and using tools like Knowledge Catalog (Dataplex) or Entropy Data for contract management.

  • Advanced knowledge of data security, compliance, and governance tooling such as Immuta and native BigQuery security controls.

  • Experience operating across hybrid or multi-data platform environments, including Palantir.

  • Google Cloud Professional Data Engineer or Professional Cloud Architect certification.

  • Databricks Certified Data Engineer Professional or Microsoft Azure data certifications, plus certifications in supporting technologies such as Power BI.

This job posting will remain open a minimum of 72 hours and on an ongoing basis until filled.

EEO/Disabled/Veterans

Job Web Development

Primary Location US-MO-Kansas City

Schedule: Full-time

Travel: No

Req ID: 265156

Job Hire Type Experienced #LI-MJ #COR

How this job compares

Set against the 5,768 open Data Engineer jobs on Olive Jobs, counted October 27, 2026.

Pay
  • This postingNot listed
  • Missouri median$115–208K/yr82 salary ranges
  • US median$62–75/hr268 hourly ranges
Openings
Olive Jobs lists 97 open Data Engineer jobs in Missouri and 5,768 across the US. 8% of them nationwide are listed as remote or flexible.
Hiring the most in Missouri
Experience
This posting asks for at least 8 years of experience — more than three in four Data Engineer postings that state a minimum ask for (median 5 years, across 5,000 postings).
Education
This posting asks for a bachelor's degree; 2,687 of the 5,768 open Data Engineer jobs (47%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on October 27, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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