Job Requirements
Washington, DC
Secret Polygraph Unspecified
Career Level not specified
Salary not specified
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Job Description
Silverthorne Advisory Group is seeking a Data Engineer - Lakehouse Analytics to design, build, and optimize modern Lakehouse platforms. In this role, you will develop scalable data pipelines, architect high-performance data solutions, and enable trusted analytics and AI-driven insights across defense organizations. This position is ideal for an engineer who enjoys solving complex enterprise challenges while working at the intersection of financial management, cloud data platforms, enterprise applications, and emerging artificial intelligence technologies.
You will work across the full data lifecycle -- from ingesting and transforming data to modeling, governing, and delivering high-quality datasets for analytics, machine learning, and operational applications. You will help automate data workflows, improve data quality and reliability, and build secure, cloud-native data solutions that support enterprise modernization initiatives.
The position will be hybrid and based in the Washington, DC metropolitan area. Onsite work locations are at the Navy Yard and Arlington, VA.
Responsibilities:
- Design, develop, and maintain scalable batch and streaming data pipelines.
- Build and optimize ETL/ELT processes to ingest data from ERP systems, financial applications, databases, APIs, event streams, and third-party platforms.
- Design, validate, test, and stabilize data layer integrations across enterprise financial systems, staging environments, Lakehouse platforms, analytics environments, and reporting solutions.
- Develop and maintain modern Lakehouse architectures that support enterprise analytics, operational reporting, and AI/ML workloads.
- Design and implement efficient data models that enable trusted, high-quality analytics and reporting.
Ensure data quality, integrity, lineage, governance, and observability through automated validation, testing, and monitoring.
- Optimize data processing performance, scalability, reliability, and cost across cloud-native environments.
- Develop reusable frameworks and standardized components for data ingestion, transformation, orchestration, and integration.
- Implement and maintain workflow orchestration using tools such as Apache Airflow or equivalent technologies.
- Build and support real-time and near-real-time data processing using streaming technologies such as Kafka or cloud-native messaging services.
- Collaborate with software engineers, solution architects, data scientists, financial management experts, and business stakeholders to deliver reliable enterprise data products.
- Implement CI/CD pipelines and Infrastructure as Code to automate deployment and management of data platform components.
- Monitor production interfaces and proactively identify opportunities to improve automation, performance, scalability, and operational resilience.
- Evaluate emerging cloud, analytics, and AI technologies to enhance enterprise data capabilities and support ongoing modernization initiatives.
- Prepare technical documentation, executive briefings, and client deliverables supporting project leadership and decision-making.
Required Skills
- Minimum of three (3) years of experience building production data engineering solutions.
- Secret clearance or higher required (can be sponsored).
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.
- Strong proficiency and hands-on coding experience with languages/technologies such as Python, Spark, Scala, JavaScript/JSON, and SQL.
- Experience designing and maintaining ETL/ELT pipelines.
- Experience with Apache Spark or equivalent distributed data processing frameworks.
- Experience working with modern Lakehouse technologies such as Databricks, Delta Lake, Apache Iceberg, or Apache Hudi.
- Experience with workflow orchestration tools such as Apache Airflow.
- Experience with cloud platforms including AWS, Azure, or Google Cloud Platform.
- Strong understanding of data modeling, data lakes, data warehouses, and dimensional modeling.
- Experience implementing data quality, validation, monitoring, and observability.
- Experience with Git, CI/CD pipelines, and software engineering best practices.
Desired Skills
- Experience with enterprise ERP (Oracle or SAP) or other DoW financial management systems.
- Experience with Snowflake, Databricks, Palantir Foundry, BigQuery, Amazon Redshift, or Microsoft Fabric.
- Experience with streaming technologies such as Apache Kafka, Amazon Kinesis, or Azure Event Hubs.
- Experience using dbt for analytics engineering and data transformation.
- Experience with Infrastructure as Code tools such as Terraform or CloudFormation.
- Experience with Docker and Kubernetes.
- Familiarity with Lakehouse table formats including Delta Lake, Apache Iceberg, or Apache Hudi.
- Experience supporting AI/ML data pipelines, feature stores, or vector databases.
- Knowledge of data governance, metadata management, security, and regulatory compliance.
- Experience supporting U.S. Department of War or other federal government modernization initiatives.
- Strong communication skills with the ability to collaborate across engineering, analytics, and business teams.
- Passion for building scalable, reusable, and secure data platforms that accelerate analytics and enterprise transformation.
Additional Details
- Compensation - We carefully consider a wide range of compensation factors, including but not limited to prior experience, skills, expertise, location, and other considerations permitted by law.
- Healthcare - We offer Health, Vision, and Dental Plans for our employees and their families.
- Retirement Plan - We invest in your future with a competitive 401(k) plan, where we match 100% of your contributions up to your first 6% and give you access to Vanguard Admiral funds.
- Paid Time Off - Based on length of service, we offer a generous amount of paid leave.
- Bonus System - As you invest in us, we invest in you. We offer bonuses to all employees who meet and exceed goals throughout the year.
- Professional Development - Support for career growth through training programs and certifications.
- Company Retreats & Team Events - Sponsored trips, team-building activities, and annual conferences related to your skillset.
You will work across the full data lifecycle -- from ingesting and transforming data to modeling, governing, and delivering high-quality datasets for analytics, machine learning, and operational applications. You will help automate data workflows, improve data quality and reliability, and build secure, cloud-native data solutions that support enterprise modernization initiatives.
The position will be hybrid and based in the Washington, DC metropolitan area. Onsite work locations are at the Navy Yard and Arlington, VA.
Responsibilities:
- Design, develop, and maintain scalable batch and streaming data pipelines.
- Build and optimize ETL/ELT processes to ingest data from ERP systems, financial applications, databases, APIs, event streams, and third-party platforms.
- Design, validate, test, and stabilize data layer integrations across enterprise financial systems, staging environments, Lakehouse platforms, analytics environments, and reporting solutions.
- Develop and maintain modern Lakehouse architectures that support enterprise analytics, operational reporting, and AI/ML workloads.
- Design and implement efficient data models that enable trusted, high-quality analytics and reporting.
Ensure data quality, integrity, lineage, governance, and observability through automated validation, testing, and monitoring.
- Optimize data processing performance, scalability, reliability, and cost across cloud-native environments.
- Develop reusable frameworks and standardized components for data ingestion, transformation, orchestration, and integration.
- Implement and maintain workflow orchestration using tools such as Apache Airflow or equivalent technologies.
- Build and support real-time and near-real-time data processing using streaming technologies such as Kafka or cloud-native messaging services.
- Collaborate with software engineers, solution architects, data scientists, financial management experts, and business stakeholders to deliver reliable enterprise data products.
- Implement CI/CD pipelines and Infrastructure as Code to automate deployment and management of data platform components.
- Monitor production interfaces and proactively identify opportunities to improve automation, performance, scalability, and operational resilience.
- Evaluate emerging cloud, analytics, and AI technologies to enhance enterprise data capabilities and support ongoing modernization initiatives.
- Prepare technical documentation, executive briefings, and client deliverables supporting project leadership and decision-making.
Required Skills
- Minimum of three (3) years of experience building production data engineering solutions.
- Secret clearance or higher required (can be sponsored).
- Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.
- Strong proficiency and hands-on coding experience with languages/technologies such as Python, Spark, Scala, JavaScript/JSON, and SQL.
- Experience designing and maintaining ETL/ELT pipelines.
- Experience with Apache Spark or equivalent distributed data processing frameworks.
- Experience working with modern Lakehouse technologies such as Databricks, Delta Lake, Apache Iceberg, or Apache Hudi.
- Experience with workflow orchestration tools such as Apache Airflow.
- Experience with cloud platforms including AWS, Azure, or Google Cloud Platform.
- Strong understanding of data modeling, data lakes, data warehouses, and dimensional modeling.
- Experience implementing data quality, validation, monitoring, and observability.
- Experience with Git, CI/CD pipelines, and software engineering best practices.
Desired Skills
- Experience with enterprise ERP (Oracle or SAP) or other DoW financial management systems.
- Experience with Snowflake, Databricks, Palantir Foundry, BigQuery, Amazon Redshift, or Microsoft Fabric.
- Experience with streaming technologies such as Apache Kafka, Amazon Kinesis, or Azure Event Hubs.
- Experience using dbt for analytics engineering and data transformation.
- Experience with Infrastructure as Code tools such as Terraform or CloudFormation.
- Experience with Docker and Kubernetes.
- Familiarity with Lakehouse table formats including Delta Lake, Apache Iceberg, or Apache Hudi.
- Experience supporting AI/ML data pipelines, feature stores, or vector databases.
- Knowledge of data governance, metadata management, security, and regulatory compliance.
- Experience supporting U.S. Department of War or other federal government modernization initiatives.
- Strong communication skills with the ability to collaborate across engineering, analytics, and business teams.
- Passion for building scalable, reusable, and secure data platforms that accelerate analytics and enterprise transformation.
Additional Details
- Compensation - We carefully consider a wide range of compensation factors, including but not limited to prior experience, skills, expertise, location, and other considerations permitted by law.
- Healthcare - We offer Health, Vision, and Dental Plans for our employees and their families.
- Retirement Plan - We invest in your future with a competitive 401(k) plan, where we match 100% of your contributions up to your first 6% and give you access to Vanguard Admiral funds.
- Paid Time Off - Based on length of service, we offer a generous amount of paid leave.
- Bonus System - As you invest in us, we invest in you. We offer bonuses to all employees who meet and exceed goals throughout the year.
- Professional Development - Support for career growth through training programs and certifications.
- Company Retreats & Team Events - Sponsored trips, team-building activities, and annual conferences related to your skillset.
group id: 91173963