Data Engineer role focused on building data pipelines, scalable data platforms, deploying ETL/ELT workflows, and guiding cross-functional teams on mission-driven projects.
Responsibilities
- Deploy and develop pipelines and platforms that organize and make disparate data meaningful.
- Help build advanced technology solutions and implement data engineering activities on mission-driven projects.
- Collaborate with and guide a multi-disciplinary team of analysts, data engineers, developers, and data consumers in a fast-paced, agile environment.
- Utilize analytical exploration and data examination while managing the assessment, design, building, and maintenance of scalable platforms for clients.
Requirements
- 5+ years of experience in database management activities, including data validation, maintenance, and optimization
- 5+ years of experience developing and maintaining scripts and code for data processing and automation
- 3+ years of experience designing, developing, operationalizing and maintaining complex data applications at enterprise scale
- 3+ years of experience creating software or managing digital platform for retrieving, parsing and processing structured and unstructured data
- 3+ years of experience building scalable ETL and ELT workflows for reporting and analytics
- Experience collaborating within a cross-functional team environment
- Ability to develop scripts and programs for converting various types of data into usable formats and helping the project team scale, monitor, and operate data platforms
- Secret clearance
- Bachelor’s degree
Technologies
- Python
- R
- SQL
- Scala
- Java
- UNIX
- Linux
- Shell scripting
- AWS
- Microsoft Azure
- Google Cloud
- Power BI
- Tableau
- Spark
- Databricks
- Hadoop
- Hive
- AWS EMR
- Kafka
- MongoDB
- Cassandra
Benefits
- Health, life, disability, financial, and retirement benefits
- Paid leave
- Professional development
- Tuition assistance
- Work-life programs
- Dependent care
- Recognition awards program
The Opportunity
Ever-expanding technology like IoT, machine learning, and artificial intelligence means more structured and unstructured data than ever before. As a data engineer, organizing data from disparate sources enables pivotal insights that support mission-critical work, from fraud detection to cancer research to national intelligence.
Clearance
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; Secret clearance is required.
Identity Statement
As part of the hiring process, you will complete an identity verification process that leverages advanced biometrics and artificial intelligence to ensure authenticity and protect against identity fraud. You are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.
Candidate AI Usage Policy
AI is a part of our daily work at Booz Allen, and we are committed to the responsible and ethical use of AI tools. The use of artificial intelligence or other tools to assist with responses during interviews is prohibited unless permission is explicitly provided.
Work Model
- Onsite: Work will primarily be performed at a Booz Allen office or customer facility, collaborating directly with colleagues and clients as required by the role.
- Hybrid: Frequent work from a Booz Allen facility with potential visits to customer facilities, depending on leadership expectations and role needs.
- Remote: Some tasks may be performed remotely, with in-person requirements possible at Booz Allen or customer facilities.
Commitment to Non-Discrimination
All qualified applicants will receive consideration for employment without regard to disability, protected veteran status, or any other status protected by applicable law.
Compensation
The projected annual compensation range is USD 77,600 to 176,000, determined by location, education, knowledge, skills, competencies, experience, contract affordability, and organizational requirements.
Nice If You Have
- Experience with Python, R, SQL, Scala, or Java
- Experience with UNIX or Linux, including basic commands and Shell scripting
- Experience with a public cloud, including AWS, Microsoft Azure, or Google Cloud
- Experience with Power BI, Tableau, or similar analytics and visualization tool
- Experience with distributed data or computing tools, including Spark, Databricks, Hadoop, Hive, AWS EMR, or Kafka
- Experience working on real-time data and streaming applications
- Experience with NoSQL implementation, including MongoDB or Cassandra
- Experience with manufacturing and supply chain data analysis, including production, procurement, inventory, logistics, supplier, and operational performance data
- Experience with Agile engineering practices
- TS/SCI clearance with a polygraph
