Data Analytics Engineer

Shadow Objects•Washington, DC

6d•Remote

About The Position

The Data Analytics Engineer is a hybrid role combining Data Analyst, Data Engineer, and Data Scientist responsibilities. This position operates with a high level of autonomy, owning projects end-to-end across functional areas. The ideal candidate is proactive, solution-oriented, and capable of identifying opportunities, reducing complexity, and delivering efficient, high-quality data solutions. This role also provides guidance to team members, helps remove roadblocks, and contributes to the continuous improvement of processes, systems, and deliverables.

Requirements

Active DoD Secret Clearance
Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, or a related field
5+ years of experience in data engineering and building data pipelines and architectures
5+ years of experience in data analysis, data mining, or business intelligence
3+ years of experience developing data solutions using Python, SQL, and/or PySpark in big data environments (e.g., Databricks, Snowflake)
Strong experience with data visualization tools (Tableau, Power BI, Qlik, Foundry) and advanced Excel (macros, pivot tables, VBA)
Experience with cloud platforms such as AWS, Azure, or Google Cloud
Familiarity with big data frameworks (Hadoop, Spark, Kafka)
Strong understanding of ETL processes, data warehousing, and BI best practices
Proven ability to analyze large datasets and communicate insights effectively
Strong problem-solving skills and attention to detail
U.S. work authorization required

Nice To Haves

Master’s degree in Data Engineering, Computer Science, or related field
Experience with DoD data platforms such as Advana and Jupiter
Familiarity with statistical methods (e.g., hypothesis testing, regression analysis)
Experience with SAP, Foundry, or advanced analytics platforms
Experience with NoSQL databases (e.g., Cassandra, MongoDB)
Knowledge of containerization tools (Docker, Kubernetes)
Experience with version control systems (Git) and Agile methodologies (Scrum, Kanban)
Prior experience in a client-facing government environment

Responsibilities

Gather, clean, and analyze complex datasets using advanced analytical techniques
Apply statistical methods to identify trends, patterns, and anomalies
Conduct exploratory data analysis (EDA) to support decision-making
Translate data findings into actionable insights for technical and non-technical stakeholders
Design, develop, and maintain ETL/ELT pipelines using Databricks and Delta Lake
Implement Medallion Architecture (Bronze, Silver, Gold) to ensure data quality and scalability
Manage data ingestion processes with a focus on traceability and governance (e.g., Collibra)
Build and maintain data pipelines within DoD environments such as Advana/Jupiter
Troubleshoot, debug, and optimize data pipelines, identifying root causes and implementing solutions
Develop dashboards, reports, and visualizations using tools such as Tableau, Power BI, Qlik, or Foundry
Create interactive dashboards and reports to support operational and strategic decisions
Ensure accuracy, quality, and usability of all data visualizations and deliverables
Collaborate with data engineers, analysts, scientists, and stakeholders to deliver integrated data solutions
Support real-time data streaming using Databricks Structured Streaming
Optimize data storage solutions leveraging Delta Lake capabilities (e.g., schema evolution, time travel)
Maintain data lineage and governance using tools such as Collibra
Ensure compliance with data security, privacy, and DoD requirements
Establish and enforce data quality standards across multiple data sources
Work closely with cross-functional teams to gather and refine requirements
Communicate findings, recommendations, and metrics clearly and professionally
Track assigned tasks and provide regular updates to leadership
Mentor junior team members and support team development initiatives