Data Engineer III

About Agile Defense At Agile Defense we know that action defines the outcome and new challenges require new solutions. That’s why we always look to the future and embrace change with an unmovable spirit and the courage to build for what comes next. Our vision is to bring adaptive innovation to support our nation's most important missions through the seamless integration of advanced technologies, elite minds, and unparalleled agility—leveraging a foundation of speed, flexibility, and ingenuity to strengthen and protect our nation’s vital interests. Requisition #: 1533 Job Tittle: Data Engineer III Location: Doral, FL Required Clearance: Top Secret Our Core Values Employees of Agile Defense are our number one priority, and the importance we place on our culture here is fundamental. Our culture is alive and evolving, but it always stays true to its roots. Here, you are valued as a family member, and we believe that we can accomplish great things together. Agile Defense has been highly successful in the past few years due to our employees and the culture we create together. What makes us Agile? We call it the 6Hs, the values that define our culture and guide everything we do. Together, these values infuse vibrancy, integrity, and a tireless work ethic into advancing the most important national security and critical civilian missions. It's how we show up every day. It's who we are. Happy - Be Infectious. Happiness multiplies and creates a positive and connected environment where motivation and satisfaction have an outsized effect on everything we do. Helpful - Be Supportive. Being helpful is the foundation of teamwork, resulting in a supportive atmosphere where collaboration flourishes, and collective success is celebrated. Honest - Be Trustworthy.Honesty serves as our compass, ensuring transparent communication and ethical conduct, essential to who we are and the complex domains we support. Humble - Be Grounded.Success is not achieved alone, humility ensures a culture of mutual respect, encouraging open communication, and a willingness to learn from one another and take on any task. Hungry - Be Eager.Our hunger for excellence drives an insatiable appetite for innovation and continuous improvement, propelling us forward in the face of new and unprecedented challenges. Hustle - Be Driven.Hustle is reflected in our relentless work ethic, where we are each committed to going above and beyond to advance the mission and achieve success. Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities Job Description Build Scalable Data & ML Infrastructure Design and implement medallion architecture (Bronze/Silver/Gold) using Databricks or reliable data processing and ML model training Develop automated data pipelines that process structured and unstructured data from multiple sources into analytics-ready formats Create robust ETL/ELT workflows using Apache Spark and modern data engineering practices for both batch and streaming data Build and maintain data quality monitoring and validation systems across the entire data and ML lifecycle Drive ML Platform Excellence Implement MLOps best practices including automated model training, validation, deployment, and monitoring using MLflow and Databricks workflows Design scalable ML inference systems that handle high-volume, low-latency predictions in production environments Create comprehensive monitoring and alerting systems for model performance, data drift, and system health Build self-service ML capabilities that enable data scientists to deploy and monitor their own models efficiently Enable Advanced Analytics & Business Intelligence Design and maintain data models that support both machine learning workloads and business intelligence requirements Create integration points between ML systems and business intelligence platforms (Tableau, PowerBI, Qlik Sense) Implement data governance standards and metadata management systems that ensure data quality and compliance Collaborate with analysts and data scientists to optimize data architecture for both predictive modeling and reporting needs Ensure Data Quality & Governance Implement comprehensive data governance frameworks including data lineage tracking, quality monitoring, and compliance controls Design and maintain data catalogs and metadata management systems that enable efficient data discovery across the organization Establish data quality standards and automated testing frameworks for both analytical and ML workloads Work with stakeholders to define data definitions, business logic, and governance policies Integrate with Enterprise Systems Build integrations with MAVEN Smart Systems (Palantir Foundry) environments to support operational and predictive analytics Connect Databricks-based systems with enterprise data warehouses, streaming platforms, and business applications Implement security and compliance controls that meet enterprise requirements while enabling self-service capabilities Collaborate with platform engineers to integrate ML systems with broader application architecture and infrastructure Education and Years of Experience Strong data engineering skills in Python, PySpark, and Spark SQL with experience implementing medallion architecture and modern data platform patterns Production ML systems experience including model deployment, monitoring, and MLOps practices in cloud environments Data architecture expertise with experience designing scalable data processing systems and implementing data governance frameworks Experience integrating with platforms such as Qlik, Tableau, PowerBI, MAVEN Smart System (Palantir), or similar. Required Skills 5+ years of technical experience, including 3+ years building production data pipelines and ML infrastructure using distributed computing platforms like Databricks. Strong data engineering skills in Python, PySpark, and Spark SQL with experience implementing medallion architecture and modern data platform patterns Production ML systems experience including model deployment, monitoring, and MLOps practices in cloud environments Data architecture expertise with experience designing scalable data processing systems and implementing data governance frameworks Experience integrating with platforms such as Qlik, Tableau, PowerBI, MAVEN Smart System (Palantir), or simil

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    {
      "text": "Job Description ",
      "content": "<div>Build Scalable Data &amp; ML Infrastructure</div>\n<div>&nbsp;</div>\n\n<li>Design and implement medallion architecture (Bronze/Silver/Gold) using Databricks or reliable data processing and ML model training&nbsp;</li>\n<li>Develop automated data pipelines that process structured and unstructured data from multiple sources into analytics-ready formats&nbsp;</li>\n<li>Create robust ETL/ELT workflows using Apache Spark and modern data engineering practices for both batch and streaming data&nbsp;</li>\n<li>Build and maintain data quality monitoring and validation systems across the entire data and ML lifecycle Drive ML Platform Excellence&nbsp;</li>\n<li>Implement MLOps best practices including automated model training, validation, deployment, and monitoring using MLflow and Databricks workflows&nbsp;</li>\n<li>Design scalable ML inference systems that handle high-volume, low-latency predictions in production environments&nbsp;</li>\n<li>Create comprehensive monitoring and alerting systems for model performance, data drift, and system health&nbsp;</li>\n<li>Build self-service ML capabilities that enable data scientists to deploy and monitor their own models efficiently Enable Advanced Analytics &amp; Business Intelligence&nbsp;</li>\n<li>Design and maintain data models that support both machine learning workloads and business intelligence requirements&nbsp;</li>\n<li>Create integration points between ML systems and business intelligence platforms (Tableau, PowerBI, Qlik Sense)&nbsp;</li>\n<li>Implement data governance standards and metadata management systems that ensure data quality and compliance&nbsp;</li>\n<li>Collaborate with analysts and data scientists to optimize data architecture for both predictive modeling and reporting needs Ensure Data Quality &amp; Governance&nbsp;</li>\n<li>Implement comprehensive data governance frameworks including data lineage tracking, quality monitoring, and compliance controls&nbsp;</li>\n<li>Design and maintain data catalogs and metadata management systems that enable efficient data discovery across the organization&nbsp;</li>\n<li>Establish data quality standards and automated testing frameworks for both analytical and ML workloads&nbsp;</li>\n<li>Work with stakeholders to define data definitions, business logic, and governance policies Integrate with Enterprise Systems&nbsp;</li>\n<li>Build integrations with MAVEN Smart Systems (Palantir Foundry) environments to support operational and predictive analytics&nbsp;</li>\n<li>Connect Databricks-based systems with enterprise data warehouses, streaming platforms, and business applications&nbsp;</li>\n<li>Implement security and compliance controls that meet enterprise requirements while enabling self-service capabilities&nbsp;</li>\n<li>Collaborate with platform engineers to integrate ML systems with broader application architecture and infrastructure&nbsp;</li>\n"
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      "text": "Education and Years of Experience ",
      "content": "\n<li>Strong data engineering skills in Python, PySpark, and Spark SQL with experience implementing medallion architecture and modern data platform patterns</li>\n<li>Production ML systems experience including model deployment, monitoring, and MLOps practices in cloud environments&nbsp;</li>\n<li>Data architecture expertise with experience designing scalable data processing systems and implementing data governance frameworks&nbsp;</li>\n<li>Experience integrating with platforms such as Qlik, Tableau, PowerBI, MAVEN Smart System (Palantir), or similar.&nbsp;</li>\n"
    },
    {
      "text": "Required Skills ",
      "content": "\n<li>5+ years of technical experience, including 3+ years building production data pipelines and ML infrastructure using distributed computing platforms like Databricks.&nbsp;</li>\n<li>Strong data engineering skills in Python, PySpark, and Spark SQL with experience implementing medallion architecture and modern data platform patterns&nbsp;</li>\n<li>Production ML systems experience including model deployment, monitoring, and MLOps practices in cloud environments&nbsp;</li>\n<li>Data architecture expertise with experience designing scalable data processing systems and implementing data governance frameworks&nbsp;</li>\n<li>Experience integrating with platforms such as Qlik, Tableau, PowerBI, MAVEN Smart System (Palantir), or simil&nbsp;</li>\n"
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