Data Engineer – Classical Statistics & Machine Learning

Job Title: Data EngineerCompany: BLN24About Us: We find strength in teamwork-a better you is a better usBLN24 is an award-winning Management Consulting Firm that supports the U.S. Federal Government in successfully achieving their mission and goals. Our service and solutions delivery start with understanding each client’s end-state, and then seamlessly integrating within each Agency’s organization to improve and enhance strategic and technical operations and deployments.Position Overview:BLN24 is seeking a mid-level Data Engineer to support a large-scale data and analytics platform modernization effort for a federal statistical agency client. This is a hybrid role: data engineering (building and maintaining the pipelines that bring data into the platform) and applied data science (using classical statistics and machine learning to analyze that data once it’s available).The ideal candidate is equally comfortable writing production-grade ingestion andtransformation code as they are designing and validating a statistical or ML model.This role works closely with SMEs across multiple program areas to understand source data, build reliable ETL/ingestion pipelines, and apply analytical methods — anomaly detection, statistical modeling, and machine learning — to support operational decision-making.Key Responsibilities:Data EngineeringDesign, build, and maintain ETL/ELT pipelines to ingest data from multiple source systems into the platform’s central data storeDevelop and maintain data ingestion workflows for both batch and near-real-time sourcesImplement data validation, cleaning, and transformation logic to ensure data quality and consistency across pipelinesWork within a modern lakehouse/cloud data architecture, optimizing pipeline performance and reliabilityBuild and maintain data models and schemas that support downstream analytics and reporting needsMonitor pipeline health, troubleshoot failures, and implement logging/alerting for data quality issuesDocument data lineage, transformation logic, and pipeline architecture for governance and reproducibilityData Science / Statistics & MLApply classical statistical methods (hypothesis testing, regression, time-series analysis, distributional comparisons) to identify trends, anomalies, and outliers in operational dataDesign and implement benchmarking approaches that compare production data against historical, modeled, or external reference valuesDevelop and evaluate machine learning models where appropriate, balancing predictive performance with interpretability for non-technical stakeholdersInvestigate flagged anomalies by digging into underlying data to identify root causes and contributing factorsWork with SMEs to translate operational questions into analytical approaches, and clearly communicate statistical/ML findings and their limitationsAccount for data sensitivity classifications and governance requirements when designing analyses and modelsCollaborate with visualization-focused team members to ensure outputs of statistical/ML work are presented clearly to stakeholdersRequired Qualifications:Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, or related field (or equivalent experience)3–5 years of experience spanning both data engineering and data science/statistical analysisStrong proficiency in Python, including experience with data engineering libraries (e.g., pandas, PySpark) and statistical/ML libraries (e.g., scikit-learn, statsmodels)Hands-on experience building and maintaining ETL/ELT pipelines, including ingestion, transformation, and validation logicSolid grounding in classical statistical methods (hypothesis testing, regression, distributional analysis) and practical machine learning techniquesExperience working with SQL and relational/distributed data systemsAbility to work within a federal data environment, including familiarity with data sensitivity tiers and access/disclosure constraintsStrong communication skills, with the ability to explain technical/statistical concepts to non-technical stakeholdersPreferred Qualifications:Prior experience supporting federal statistical agencies or other federal data programsFamiliarity with Databricks or modern lakehouse architectures (Spark, Delta Lake, etc.)Experience with workflow orchestration tools (e.g., Airflow, Databricks Workflows)Experience designing anomaly-detection or outlier-detection approaches beyond standard threshold-based methodsExposure to disclosure avoidance concepts or working with regulated/protected government dataExperience working across multiple coding environments (Python, R, SAS) within the same analytics platformBackground in requirements gathering or systems design for enterprise data platformsWork Environment:Contract position supporting a federal agency data modernization engagementCollaborative, cross-functional environment working alongside data engineers, data scientists, architects, and program SMEsRequires U.S. citizenship and ability to obtain a public trust or other clearance/suitability determination typical of federal contractor engagements What BLN24 brings to the Game:BLN24 benefits are game changing. We like our team to play hard and that means they need to be taken care of — physically, financially, and emotionally. We make sure to keep them in the game by giving them access to generous medical, dental, and vision plans.You can join one of the fastest growing companies headquartered in the Washington DC Metro Area.  We give you the opportunity to work in different sectors, so you have the chance at variety while maintaining stability.Flexibility at BLN24 allows each individual the opportunity to balance quality work and their personal lives. Depending on projects, we allow remote working opportunities so you can always be in the game no matter where you call home.BLN24 is an Equal Opportunity Employer. We believe people are our strength and understand diverse talents are key to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. In accordance with applicable law, we make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as any mental health or physical disability needs.