Lead, Analytics & Data Engineering - TS/SCI Required
Role details
Job location
Tech stack
Job description
- Lead and oversee a multidisciplinary team of data engineers and data scientists.
- Collaborate with business/functional stakeholders to understand processes, define analytical requirements, and communicate results.
- Mentor junior team members across data engineering and data science disciplines.
- Build and maintain strong relationships with stakeholders to ensure alignment with organizational goals.
- Manage delivery of projects, including timelines, deliverables, resources, and quality.
- Provide technical and process consulting in support of mission outcomes.
Data Engineering & Platform Modernization
- Lead the modernization, maintenance, and scaling of data pipelines, data warehouses, and related infrastructure.
- Contribute to the organization's data engineering and advanced analytics strategy, roadmap, and data governance practices.
Advanced Analytics & Modeling
- Frame and scope analytical problems; integrate, consolidate, and analyze complex datasets.
- Guide development and validation of models using machine learning, simulation, causal, rule-based, or statistical methods.
Analytics Delivery & Communication
- Translate analytical results into dashboards, visualizations, and analytic narratives that support decision-making.
- Provide timely analysis and reporting in a fast-paced, client-focused environment.
- Advise non-technical stakeholders on interpreting and applying data products, dashboards, and reports.
Requirements
- Bachelor's degree in data science, mathematics, statistics, economics, computer science, engineering, or a related quantitative discipline is required; advanced degree preferred.
Experience:
- 5-10 years of relevant experience, with at least 2 years leading data engineering or data science teams as a technical lead or task lead.
- Demonstrated experience delivering complex data pipelines and analytical projects in client-focused environments.
Technical Skills:
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Proficiency in Python and SQL is required. Strong working knowledge of relational databases, including database optimization, schema design, and connecting analytic products to data sources.
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Experience with designing, building, and maintaining ETL/ELT pipelines and data integration workflows in support of scalable analytics solutions.
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Familiarity with core data science and analytics libraries in Python to support modeling, analysis, and feature engineering.
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Experience building visualizations, dashboards, and lightweight analytic applications to communicate findings and drive business impact using modern platforms (e.g., Tableau, Streamlit, or similar tools).
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Exposure to additional analytic, visualization, and programming tools (e.g., Qlik, Power BI, RShiny, Plotly, Java, R), demonstrating the ability to adapt across technologies.
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Familiarity with data engineering and data science methods including data transformation, feature engineering, predictive analytics, and unstructured text analysis.
Leadership and Interpersonal Skills:
- Strong written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Demonstrated ability to mentor and develop junior team members across data engineering and data science disciplines.
- Strong stakeholder management skills, including the ability to build trusted relationships and balance modernization efforts with stakeholder-facing delivery.
- Ability to work in a fast-paced, solutions-oriented environment while delivering high-quality products.
- Strong analytical, problem-solving, and organizational skills with a focus on practical outcomes and mission impact.
This position requires an active TS/SCI security clearance with polygraph. Applicants with TS/SCI who are eligible for polygraph are encouraged to apply and will be sponsored for upgrade.
Applicants must meet eligibility requirements for a U.S. Government security clearance. Only US Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work.