Guidehouse

Senior Data Engineer

Full-time · US - TX, San Antonio
✓ Verified live on the employer's own system · added 36 days ago
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Mid-level · 3+ yrs exp

Requirements

Education: Bachelor's degree

Experience: 3+ years

Skills & tools

Cloud PlatformsDatabricksData AnalysisOperationsPythonSQLDefenseSecurity Clearance
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Full job description

Job Family: Data Engineering & Architecture Consulting Travel Required: None Clearance Required: Ability to Obtain Public Trust

What You Will Do: Design, build, and operate Azure Lakehouse architectures using Azure Databricks, Azure Data Lake Storage (ADLS Gen2), Azure Synapse Analytics, and Azure Data Factory to support analytical and operational workloads. Develop, maintain, and optimize scalable ETL/ELT pipelines using Databricks Workflows, Spark jobs, and Delta Lake to ensure reliability, performance, and enterprise-grade data quality.

Process large-scale structured and unstructured datasets using optimized batch and streaming pipelines leveraging Apache Spark, Delta Lake, Python, SQL, and Scala. Collaborate with cross-functional teams to deliver enterprise solutions on Azure and support production deployments, monitoring, and operational excellence. Implement data quality, performance tuning, and cost-optimization practices for data platforms and pipelines.

What You Will Need: Must be able to OBTAIN and MAINTAIN a Federal or DoD "Public Trust" security clearance; candidates must obtain approved adjudication of clearance prior to onboarding with Guidehouse. Candidates with an ACTIVE "Public Trust" or higher-level clearance are preferred. Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or equivalent experience.

FIVE (5) or more years of experience as a Data Engineer, including THREE (3) years delivering enterprise solutions on Azure, specifically using Azure Databricks and Azure-native data services. Hands-on experience designing, building, and operating Azure Lakehouse architectures using Azure Databricks, ADLS Gen2, Azure Synapse Analytics, and Azure Data Factory.

Experience in Apache Spark, Delta Lake, Python, SQL, and Scala, with demonstrated ability to process large-scale structured and unstructured datasets using optimized batch and streaming pipelines. Experience designing, developing, and maintaining scalable ETL/ELT pipelines using Databricks Workflows, Spark jobs, and Delta Lake, ensuring reliability, performance, and data quality at enterprise scale.

Experience with real-time and batch data processing. What Would Be Nice To Have: Azure certifications (for example, Azure Data Engineer) or equivalent cloud/data platform certifications. Experience implementing CI/CD for data engineering, MLOps pipelines, or data platform automation.

Familiarity with data governance, observability, and cost-optimization practices at scale. #LI-DNI

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