Full Stack ETL Developer
Job Description
We are seeking a highly experienced Senior Data & Software Engineer to design, develop, and operate large-scale data platforms and mission-critical applications. This role combines data engineering, full-stack software development, cloud architecture, graph databases, MLOps, and DevSecOps.
The ideal candidate will have experience building highly scalable data systems, ETL/ELT pipelines, graph and NoSQL solutions, cloud-native applications, and modern user interfaces while operating within secure, regulated environments.
- Design and maintain enterprise-grade batch and real-time ETL/ELT pipelines
- Develop front-end applications using React, Next.js, WebGL, or similar technologies
- Develop backend services and microservices using Python, Java, Scala, C/C++, and REST APIs
- Design and operate large-scale big data, NoSQL, relational, and graph database solutions
- Build and optimize graph databases and traversal capabilities using technologies such as Gremlin, Cassandra, Neo4j, JanusGraph, and TinkerPop
- Develop high-performance data processing pipelines using PySpark, Lambda, Step Functions, NiFi, and related technologies
- Design data models, partitioning/sharding strategies, indexing, stream processing, and record aggregation workflows
- Develop and maintain cloud-native solutions across AWS and other cloud platforms
- Build and operate Kubernetes and Docker-based infrastructure
- Develop CI/CD, Infrastructure as Code, DevSecOps, and MLOps pipelines
- Implement data security, encryption, auditing, LDAP-based access controls, and data governance
- Support federal security, compliance, and accreditation requirements
- Collaborate across engineering and stakeholder teams to develop technical strategies that meet mission requirements
- Experience designing and operating large-scale data systems supporting billions to trillions of records/events
- Strong experience with ETL/ELT, batch and real-time data pipelines, and distributed data processing
- Full-stack development experience with React/Next.js and backend technologies such as Python, Java, or Scala
- Experience with REST APIs and microservices architectures
- Experience with Docker, Kubernetes, CI/CD, and Infrastructure as Code
- Experience with AWS or other major cloud platforms
- Strong experience with relational, NoSQL, and graph databases
- Experience with technologies such as DynamoDB, Cassandra, PostgreSQL, MongoDB, Neo4j, ELK, MariaDB, MinIO, and S3
- Experience with Spark/PySpark, Lambda, Step Functions, and stream-processing workflows
- Knowledge of graph technologies such as Apache Gremlin, TinkerPop, and JanusGraph
- Experience with probabilistic/statistical modeling, including risk scoring, Bayesian inference, and Monte Carlo simulation
- Experience developing MLOps pipelines for large-scale applications
- Experience with data security, governance, encryption, auditing, and LDAP
- Experience implementing DevSecOps and Agile development practices in production environments
- Experience with federal security, regulatory, compliance, and accreditation requirements
- Experience working with structured, semi-structured, and unstructured data formats including JSON, CSV, AVRO, Parquet, and Protocol Buffers
- #CJ
- Experience designing and operating cloud-native data platforms within Intelligence Community environments
- Experience with AWS ECS, Fargate, EMR, and multi-account AWS environments
- Experience managing AWS Organizations, Organizational Units (OU), and Service Control Policies (SCP)
- Experience with enterprise data catalogs, Policy Decision Points (PDPs), and data management services
- Experience developing MLOps and large-scale data processing pipelines within secure government environments
- Understanding of IT Service Management (ITSM) and SLA metrics
- Experience presenting complex technical solutions and requirements to diverse technical and non-technical audiences
- #CJ
- Must be fully cleared with a recent polygraph
- Must be willing and able to work fully onsite at the location listed in this posting
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
