Overview:
LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.
Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.
Responsibilities:
- Performs data engineering and data analysis to create, store, locate, retrieve, analyze, manage, and share documentation/artifacts.
- Leads and develops data products within the system/software development life cycle from requirements definition, to architecture, design, implementation, and testing, through deployment and operations, and support.
- Defines and develops techniques to integrate, consolidate, and structure data for analytical use, including the ability to inform on data aggregation and associated security implications, and the ability to leverage logical data models to support data source mappings.
- Identifies data migration strategies to transition data from legacy systems and technologies to advanced, enterprise-based solutions.
- Performs assessments relative to data architecture, design, and implementation, and identifies system impacts associated with new requirements, and requirements changes.
- Works in collaboration with developers, data scientists, and other engineers to facilitate data movement and security both on-prem and in the cloud.
- Contributes to technical collaboration with internal and external stakeholders.
Qualifications:
Minimum Qualifications:
- Active SECRET clearance required
- Bachelor’s Degree in a STEM or related field
- Minimum 3-years of demonstrated experience with enterprise data management solutions and platforms in the areas of master data management, data quality management, data governance, metadata management, Extract-Transform-Load (ETL), data warehousing, and data lakes
- Minimum 2-years of experience modeling and managing structured and unstructured data including photos/images, physical specifications/technical diagrams
- Experience leading legacy data integration and remediation (facades, strangler approaches, etc)
- Deep understanding of different integration patterns and best practices such as events, synchronous vs asynchronous messaging, peer-to-peer, publish-to-subscribe, distributed logs, and RESTful APIs
- Must possess and maintain an active Secret Security Clearance.
PREFERRED EXPERIENCE/SKILLS:
- Demonstrated experience working with relational(sql) database management systems, normalizing complex data to optimize for writing and reading as well as designing efficient queries for operational and analytical purposes.
- Demonstrated experience working with messaging platforms (Kafka, Rabbitmq, Redis queueing) to create data pipelines that allow applications to operate as loosely coupled components and facilitate easy on-boarding of new features.
- Has worked with message encoding languages such as Protobuf, Avro, JSON, and can select appropriate solution for a given message stream.
- Demonstrated experience working with specific non-relational databases such as Apache Druid, Cassandra, and AWS Simple Storage Solution(S3). Should be able to explain when to use these solutions and instead of relational database solutions.
- Some experience working with distributed, high-volume database solutions such as Apache Hadoop, Apache Spark.
- Proficiently in scripting data transformations jobs and writing API servers with Python
- Has worked with domain experts in a field they did not have proficiency to deliver value to customers
- Demonstrated experience working with Kubernetes (k8s) and containerization (docker).
The target salary range for this position is $122,209 - $211,317
The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.
