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This listing doesn't post a salary. Most similar roles pay
$135,000–$213,000.
Based on 240 similar postings.
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About Booz Allen Hamilton
Booz Allen Hamilton is a management and technology consulting firm that provides analytics, digital, engineering, and cybersecurity solutions primarily to U.S. government agencies and commercial clients. Industry: Management & Technology Consulting
Booz Allen Hamilton currently has
1662 open roles
on FindRole.
Listed pay typically runs
$86,800–$198,000
across 904 roles with salary data.
The Data Engineering Senior Manager leads a team of five experienced engineers to build and operate data pipelines powering enterprise analytics for a high-visibility business-critical program. This leadership role involves setting technical direction, aligning priorities, and establishing engineering standards while empowering the team to operate with autonomy. You will translate business priorities into actionable roadmaps, ensuring the delivery of reliable, scalable data products. Key responsibilities include managing the technical roadmap, improving delivery predictability, and advancing DataOps practices like CI/CD, automated testing, and data quality monitoring. The role requires proficiency in Databricks, Apache Spark, Python, and SQL. You will work with structured and unstructured data to develop ETL/ELT pipelines, utilizing medallion architecture and Delta Lake to solve complex data engineering and production challenges.
Lead, coach, and develop a team of five data engineers to foster a culture of accountability and continuous improvement.
Own the team’s delivery commitments, technical roadmap, operating rhythm, and stakeholder communications.
Provide technical direction for data pipelines and enterprise data products developed in Databricks.
Establish engineering standards for architecture, code quality, testing, documentation, deployment, security, and production support.
Guide architecture and design decisions while evaluating technical tradeoffs to resolve complex engineering challenges.
Create reusable engineering patterns and automation to improve delivery speed, reliability, and scalability.
Advance DataOps practices including CI/CD, automated testing, data quality monitoring, and incident response.
Partner with stakeholders to translate strategic business objectives into actionable technical plans and roadmaps.
What we're looking for
U.S. citizenship is required.
10+ years of experience in data engineering, data science, data platform development, or enterprise data delivery.
Experience managing or leading teams of experienced technical professionals, including coaching, performance feedback, and delivery accountability.
Experience developing and operating data solutions using Databricks and Apache Spark.
Experience designing and maintaining scalable ETL and ELT pipelines, including curated or gold-layer data products.
Experience with data modeling, data warehousing, processing structured/unstructured data, Python, and SQL.
Experience with software engineering and DataOps practices, including source control, code review, automated testing, CI/CD, monitoring, and production support.