Senior Data Engineer

Jobtailor

Bethesda (MD)

On-site

USD 140,000 - 190,000

Full time

14 days+

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Job summary

Jobtailor is seeking a highly skilled Data Engineering Lead in Bethesda to design, build, and optimize scalable data platforms for analytics and AI/ML workloads. You will work with Elasticsearch/OpenSearch and graph databases, ensuring high performance and scalable ingestion in a Kubernetes environment.

The role requires deep data modeling, large-scale ETL/ELT pipelines, and collaboration with cross-functional teams.

Qualifications

Bachelor's degree in Computer Science, Data Engineering, or related field with 12–15 years of experience or Master with 10–13 years.
Active Top Secret/SCI clearance and ability to obtain a Polygraph.
Elasticsearch/OpenSearch architecture, index design, mappings, analyzers, and query optimization.
Graph databases such as JanusGraph, Neo4j, TigerGraph, Neptune, or Memgraph.
Data modeling for hierarchical and highly connected datasets.
Large-scale ETL/ELT pipeline development.
Kubernetes deployment and operations for stateful data services.
Python or Java for data engineering and automation.

Responsibilities

Design, develop, and optimize scalable data management solutions for analytics and AI/ML workloads.
Build and maintain Elasticsearch and graph-based data platforms for storage, discovery, and analysis of hierarchical data.
Design and optimize Elasticsearch indices for high-performance search and analytics on large structures.
Design, implement, and maintain a graph data store for hierarchical graphs with high throughput.
Develop scalable ingestion pipelines for graph analytics workloads.
Collaborate with infra and platform teams to deploy Elasticsearch and graph services in Kubernetes with cloud-native tech.
Partner with data scientists and AI/ML engineers to manage datasets throughout the data lifecycle.
Develop automated data loading, transformation, validation, and QA pipelines for production analytics.
Optimize graphs and search infrastructure for high availability and performance at scale.
Work with software engineers to integrate graph and search services into microservices.

Skills

Python

Java

Data Modeling

ETL/ELT Pipelines

Kubernetes

Distributed Storage

Graph Analytics

Elasticsearch/OpenSearch

Education

Bachelor's degree in Computer Science or Data Engineering

Master's degree in related field

Tools

Elasticsearch/OpenSearch

JanusGraph/Neo4j/TigerGraph/Amazon Neptune/Memgraph

Kubernetes

Cloud-Native Technologies

Automated Testing Tools

Job description

Design, develop, and optimize scalable data management solutions supporting advanced analytics and AI/ML workloads.
Build and maintain Elasticsearch and graph-based data platforms that enable efficient storage, discovery, and analysis of complex hierarchical data.
Design and optimize Elasticsearch indices to efficiently manage large-scale hierarchical classification structures, ensuring high-performance search, aggregation, and update operations.
Design, implement, and maintain a graph data store supporting hierarchical graph structures optimized for large, dense batch updates and high-throughput analytics.
Develop scalable ingestion pipelines that support scalable graph analytics.
Design data schemas, indexing strategies, and partitioning approaches to maximize query performance, scalability, and storage efficiency.
Collaborate with infrastructure and platform engineering teams to deploy, operate, and optimize Elasticsearch and graph database services in a Kubernetes environment using cloud-native technologies.
Partner with Data Scientists and AI/ML engineers to ingest, curate, manage, analyze, and securely expunge datasets throughout the data lifecycle.
Develop automated data loading, transformation, validation, and quality assurance pipelines supporting production analytics workflows.
Optimize graph and search infrastructure for high availability, resilience, and performance under large-scale analytical workloads.
Collaborate with software engineers and system architects to integrate graph and search services into microservice-based applications.
Participate in SAFe Agile development activities, including sprint planning, design reviews, architecture discussions, and technical demonstrations.
Foster a culture of innovation, collaboration, and professional development within the team.
Ensure sound engineering practices, compliance with policies, and delivery of high-quality software.
Coordinate with test teams to develop and monitor automated system integration tests.
Engage with cross-functional teams to identify and develop high-value integrations with other systems/applications.
Provide specific input to the software components of system design to include hardware/software trade-offs, software reuse, use of COTS/GOTS in place of new development, and requirements analysis and synthesis from system level to individual software components.

Requirements

Bachelors degree in Computer Science, Data Engineering, or related field and 1215 years of relevant experience, or Masters with 1013 years of experience.
Must possess an Active Top Secret/SCI clearance and ability to obtain and maintain a Polygraph.
Elasticsearch/OpenSearch architecture, index design, mappings, analyzers, and query optimization.
Graph databases such as JanusGraph, Neo4j, TigerGraph, Amazon Neptune, or Memgraph.
Data modeling for hierarchical and highly connected datasets.
Large-scale ETL/ELT pipeline development.
Kubernetes deployment and operations for stateful data services.
Distributed storage systems and high-volume data ingestion.
Python or Java for data engineering and automation.

Core Competencies

Demonstrates expertise in designing and optimizing scalable data management solutions, particularly with Elasticsearch and graph databases, while ensuring high performance and efficiency in data processing and analytics. Proficient in developing automated data pipelines and collaborating with cross-functional teams to enhance data lifecycle management.

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