Job Description

The Data Engineer will design, build, and maintain the core client data infrastructure and pipelines necessary to ingest, process, store, and transform data for various consumers. Develop and operate automated, end-to-end data pipelines, create and maintain data models and schemas, and contribute to the overall scalability, reliability, and security of the data platform. Implement data processing frameworks and technologies, design and optimize data storage solutions, and develop data transformation logic to support analytics requirements. Implement data quality checks and validation procedures, establish data lineage tracking mechanisms, and troubleshoot data pipeline issues. Collaborate with data scientists and analysts to understand data requirements, work with security teams to implement data protection measures, and stay current with data engineering technologies and best practices. Document data architecture and pipelines, participate in data governance activities, and contribute to continuous improvement of data engineering processes.

Must have:

• 8 years of experience in data engineering, data pipeline design, and management
• Must meet DoD 8140 requirements
• Bachelor’s degree (or 4 years of additional equivalent experience) in IT, Cybersecurity, Computer Science, Information Systems, Data Science, Software Engineering

Security Clearance:

• Active TS/SCI clearance

Job Description

The Data Architect will be responsible for designing and governing the entire data ecosystem. The architect will establish the enterprise data model, define standards for data storage (e.g., data lakes, warehouses, databases), and design the architecture for data ingestion, processing pipelines (ETL/ELT), and data access. They will work closely with the GRC and security teams to ensure data governance, data quality, and data protection policies are designed into the architecture from the start. The Data Architect's primary goal is to ensure that the data is findable, accessible, interoperable, and reusable (FAIR), enabling advanced analytics and AI/ML at scale. 

Must have:

• Bachelor’s degree (or 4 years of additional equivalent experience) in IT, Cybersecurity, Computer Science, Information Systems, Data Science, Software Engineering
• Minimum 8 years of experience designing enterprise data architectures and models

Security Clearance:

• Active TS/SCI clearance

Job Description

The Data Architect will be responsible for designing and governing the entire data ecosystem. The architect will establish the enterprise data model, define standards for data storage (e.g., data lakes, warehouses, databases), and design the architecture for data ingestion, processing pipelines (ETL/ELT), and data access. They will work closely with the GRC and security teams to ensure data governance, data quality, and data protection policies are designed into the architecture from the start. The Data Architect's primary goal is to ensure that the data is findable, accessible, interoperable, and reusable (FAIR), enabling advanced analytics and AI/ML at scale. 

Must have:

• Bachelor’s degree (or 4 years of additional equivalent experience) in IT, Cybersecurity, Computer Science, Information Systems, Data Science, Software Engineering
• Minimum of 8 years of experience designing enterprise data architectures and models

Security Clearance:

• Active TS/SCI clearance

Job Description

The Data Architect will be responsible for designing and governing the entire data ecosystem. The architect will establish the enterprise data model, define standards for data storage (e.g., data lakes, warehouses, databases), and design the architecture for data ingestion, processing pipelines (ETL/ELT), and data access. They will work closely with the GRC and security teams to ensure data governance, data quality, and data protection policies are designed into the architecture from the start. The Data Architect's primary goal is to ensure that the data is findable, accessible, interoperable, and reusable (FAIR), enabling advanced analytics and AI/ML at scale. 

Must have:

• Bachelor’s degree (or 4 years of additional experience) in IT, Cybersecurity, Computer Science, Information Systems, Data Science, Software Engineering
• 8 years of experience designing enterprise data architectures and models

Security Clearance:

• Active TS/SCI clearance

Job Description

The Solutions Architect is the primary customer-facing architect, responsible for translating the warfighter's complex mission needs into feasible, end-to-end technical solutions on the Platform. Work directly with mission owners and the "Solution Consultant" team during the intake process to understand requirements, design solution blueprints, and ensure the proposed approach effectively leverages the platforms existing services and capabilities. Design the high-level integration patterns, data flows, and service compositions required to solve a specific mission problem, providing the detailed architectural guidance necessary for development teams to begin implementation.

Must have:

• 8 years of experience designing end-to-end technical solutions for enterprise customers
• Bachelor’s degree (or an additional 4 years of experience) in IT, Cybersecurity, Computer Science, Information Systems, Data Science, Software Engineering, or related field

Security Clearance:

• Active TS/SCI clearance

Job Description

The Solution Engineer  will lead technical requirement gathering and solutioning for customer use cases. Provision tools, resources, and ensure alignment with customer needs. Lead the customer use case intake process, working with customers to understand their requirements and objectives. Coordinate with technical teams to develop solutions for customer needs, ensuring proposed solutions are feasible and align with the System's capabilities. Manage the intake pipeline, prioritizing and scheduling new use cases based on organizational priorities and resource availability. Develop and maintain intake process documentation and templates. Facilitate solutioning workshops with customers and technical teams. Work with the service catalog manager to identify opportunities for new or enhanced services based on recurring customer needs. Track and report on intake metrics, including volume, cycle time, and customer satisfaction. Collaborate with the customer success team to ensure smooth handoff of new use cases for implementation. Stay informed about the System's capabilities and roadmap to effectively guide customers during the intake process.

Must have:

• 8 years of experience gathering technical requirements, solutioning, and managing customer cases in technical enterprise settings.
• Demonstrated ability to translate complex business and mission needs into feasible technical solutions, facilitate cross-functional collaboration, and ensure successful end-to-end solution delivery.
• Bachelor’s degree (or an additional 4 years of experience).

Security Clearance:

• Active TS Clearance

Job Description

The Performance Reporting Architect will conduct comprehensive systems engineering activities to support the client platform. Translate customer requirements into detailed system designs, develop and analyze system alternatives to recommend optimal solutions, and define user roles and personas to establish appropriate system access controls. Create and maintain system models, diagrams, and technical documentation throughout the development lifecycle. Perform trade studies to evaluate technical options against requirements, develop verification and validation procedures to ensure system compliance, and participate in technical reviews to assess design progress and quality. Collaborate with cross-functional engineering teams to ensure seamless system integration, identify and mitigate technical risks before they impact delivery, and support the resolution of technical issues throughout the system lifecycle. Implement requirements traceability to verify all customer needs are addressed, conduct system performance analysis to optimize operations, and develop technical specifications for system components. Evaluate emerging technologies for potential system enhancements, support system testing activities, and contribute to continuous improvement of systems engineering processes and methodologies.

Must have:

• 8 years of experience in systems engineering for complex technical platforms
• Demonstrated ability to translate requirements into detailed system designs and support integration and documentation throughout the system lifecycle
• Skilled in risk mitigation and performance optimization
• Must meet DoD 8140 requirements
• Bachelor’s degree (or an additional 4 years of equivalent experience) in IT, Cybersecurity, Computer Science, Information Systems, Data Science, Software Engineering

Security Clearance:

• Active TS/SCI clearance

Job Description

The Data Security Engineer will ensure the security and compliance of the platform and its associated data tools. Implement data protection measures, manage user access and permissions for data tools, and ensure adherence to all applicable data security policies and regulations in collaboration with the data governance team. Design and implement data security controls and safeguards, conduct security risk assessments for data systems, and develop data classification and handling procedures. Configure and manage data access control systems, monitor for unauthorized data access attempts, and respond to data security incidents. Implement data encryption solutions for data at rest and in transit, collaborate with compliance teams to ensure regulatory requirements are met, and provide guidance on secure data handling practices. Perform security reviews of data integrations and sharing arrangements, maintain documentation of data security controls, and stay current with data security technologies and threats. Develop and deliver data security awareness training, participate in security audits and assessments, and implement data loss prevention strategies.

Must have:

• 8 years of experience implementing security controls for data platforms in large environments
• Must meet DoD 8140 requirements
• Bachelor’s degree (or an additional 4 years of experience) in IT, Cybersecurity, Computer Science, Information Systems, Data Science, Software Engineering, or related field

Security Clearance:

• Active TS/SCI clearance

Job Description

The Data Architect is responsible for designing and governing the entire data ecosystem of the Platform. Establish the enterprise data model, define standards for data storage (e.g., data lakes, warehouses, databases), and design the architecture for data ingestion, processing pipelines (ETL/ELT), and data access. Work closely with the GRC and security teams to ensure data governance, data quality, and data protection policies are designed into the architecture from the start. The Data Architect's primary goal is to ensure that data on the platform is findable, accessible, interoperable, and reusable (FAIR), enabling advanced analytics and AI/ML at scale.

Must have:

• 4 years of experience designing enterprise data architectures and models
• Bachelor’s degree (or an additional 4 years of experience) in IT, Cybersecurity, Computer Science, Information Systems, Data Science, Software Engineering, or related field

Security Clearance:

• Active TS/SCI clearance

Job Overview: As a GCP Data Pipeline Developer & BigQuery Data Engineer, you will be responsible for designing, developing, and maintaining data pipelines on Google Cloud Platform (GCP). Your role will involve working with BigQuery to analyze and optimize large datasets, as well as implementing ETL processes to ensure data quality and integrity. Proficiency in foundational GCP services, BigQuery, data engineering principles, SQL, and PySpark will be essential for success in this position. Additionally, experience with ETL tools such as Qlik Data Integration or FiveTran would be a valuable asset in this role.

In this role, you will have the opportunity to work on complex data projects that require a deep understanding of cloud-based data processing and analysis. Your expertise in GCP and BigQuery will be crucial in developing efficient data pipelines that meet the organization's data processing needs. Strong SQL skills will be necessary for querying and manipulating data within BigQuery, while experience with PySpark will enable you to perform advanced data transformations and analytics. Overall, your ability to leverage these tools and technologies effectively will be key to driving data-driven decision-making within the organization.

Key Responsibilities:

• Develop and maintain GCP data pipelines.
• Design and optimize BigQuery data structures.
• Utilize SQL and PySpark for data processing.
• Collaborate with team members on data engineering projects.
• Implement ETL processes using tools like GCP Dataflow, Qlik Data Integration, or FiveTran.

Here's What You Need:

• Proficiency in foundational GCP services.
• Strong experience with BigQuery.
• Solid understanding of data engineering principles.
• Advanced SQL skills for querying and manipulating data.
• Experience with PySpark for data transformations and analytics.
• Familiarity with ETL tools such as Qlik Data Integration or FiveTran.
• Ability to design and implement scalable data solutions.
• Strong analytical and problem-solving skills.
• Excellent collaboration and communication skills.
• US Citizenship required, No Dual Citizenship

Bonus points if you have:

• Experience with other cloud platforms and big data technologies.
• Previous experience in a similar role within a data-driven organization.
• Certifications related to GCP, BigQuery, or data engineering.

Job Description:

The Senior Data & Software Engineer works with a small team to build complex data flows for a custom application. Successful candidate will have advanced Python programming skills, familiarity with Java, an understanding of data security, privacy, governance and compliance principles, and a demonstrated history of building production data pipelines and ETL workflows at scale.

Work you'll do:

• Work with stakeholders to understand data requirements, assess feasibility, and design appropriate solutions with minimal oversight.
• Leverage strong problem-solving and debugging skills for data quality issues, pipeline failures, and performance bottlenecks.
• Leverage a background in large-scale data migration or platform modernization efforts.
• Contribute to data engineering documentation, best practices, and design patterns.

What you'll need:

• Minimum of 5 years' experience with the following:
  • Apache Spark & PySpark
  • Using orchestration tools to deploy data pipelines, including configuring and updating Spark Jobs
  • Advanced Python skills (including Pandas & NumPy)
  • Building end-to-end data pipelines leveraging Python
  • Docker, Podman
  • AWS S3, Lambda & Step functions
  • Apache Iceberg, Airflow, etc.
  • SQL (with Trino)
  • NoSQL, DynamoDB
  • Containerizing and deploying applications in cloud environments like AWS
  • Working with MySQL and PostgreSQL including performance tuning, schema design, and query optimization for complex, analytical workloads
  • Leveraging industry standard tools for code control (Git, IaaC control, etc.)
  • Working with data catalogs, tracking data lineage, and handling a variety of data formats, including Geospatial
  • Using Bash scripting for automation and data processing tasks
  • Integrating Al/ML services and models

Bonus points if you have:

• Unity Catalog OSS, Apache Polaris
• Apache Superset
• Terraform or CloudFormation
• OpenLineage
• H3, PostGIS

Security clearance:

• Active TS/SCI with Poly security clearance is required

As the Data Governance Manager for Data Products, you will be a hands-on leader responsible for ensuring that all data assets on a data platform are trusted, discoverable, and governed. You will be the subject matter expert on the team that handles the critical "last mile" of the data lifecycle. Your mission is to implement the policies and automated processes that embed governance directly into our data products, making them reliable and ready for mission use.

Responsibilities:

• Drive the implementation of data governance and data management policies across all data products.
• Oversee the day-to-day management of the enterprise data catalog (e.g., Collibra, Atlas), ensuring all data products are accurately registered with complete metadata and lineage.
• Define, implement, and monitor data quality rules and metrics for data products, ensuring they meet established Service Level Agreements (SLAs).
• Collaborate with data pipeline teams to ensure "governance is baked in" from the start of the development lifecycle.
• Act as a key point of contact for data stewards and data consumers, helping to resolve data quality issues and improve data literacy.
• Mentor junior analysts on data governance principles, data quality best practices, and catalog management.
• Develop and maintain documentation for data standards, governance processes, and data product specifications.

Must have: 

• 5+ years of experience in data governance, data management, or data quality assurance.
• Proven, hands-on experience with enterprise data cataloging and governance platforms (e.g., Collibra, Alation, Atlas, Purview).
• Deep understanding of data governance frameworks, metadata management, and data quality principles.
• Strong proficiency in SQL for data analysis and validation.
• Experience leading small teams or mentoring junior staff in a technical environment.
• US Citizenship (No Dual Citizenship). 

Nice to have:

• Experience working in high-security DoD environments (e.g., SIPR, JWICS).
• Familiarity with data quality tools like Great Expectations.
• Proficiency with Python for automation and data analysis.
• Experience working on a data platform built on Databricks or Snowflake.
• Certified Data Management Professional (CDMP) or similar certification.

Security Clearance:

• Active TS or TS/SCI clearance

The work:

As a Data Engineer, you will be responsible for designing, developing, and maintaining data solutions for data generation, collection, and processing.

Key Responsibilities:

The work: 

Key Responsibilities:

#LI-DataAI

The work: 

• Pipeline Architect: Design, build, and maintain scalable end-to-end data pipelines using Databricks, Spark, and related technologies. 
• Transformation Titan: Develop efficient data processing and transformation workflows to support analytics and reporting needs. 
• Integration Hero: Integrate diverse data sources including APIs, databases, and cloud storage into unified datasets. 
• Collaboration Champion: Work closely with cross-functional teams (data science, analytics, business units) to design and implement data solutions that align with business goals. 
• Quality Guardian: Implement robust validation, monitoring, and observability processes to ensure data accuracy, completeness, and reliability. 
• Automation Avenger: Contribute to data governance, security, and automation initiatives within the data ecosystem. 
• Cloud Commander: Leverage AWS services (e.g., S3, Glue, Lambda, Redshift) to build and deploy data solutions in a cloud-native environment. 

Here’s what you need: 

• Experience with cloud-based ETL services (e.g. AWS Glue, Google Cloud Dataflow, Azure Data Factory) 

• Experience with Cloud data warehousing technologies (e.g. Amazon Redshift, Google BigQuery, Snowflake) 

• Experience with Python, SQL, Spark, and PySpark 

• Experience with data platforms like Databricks, Palantir, and Snowflake 

• Familiarity with data orchestration and data quality processes 

Bonus points if you have:

• Experience working with federal clients 

• Experience with Docker/Kubernetes Hadoop/Spark, NiFi, ELK stack 

• Experience with Agile / Scrum 

• Experience with COTS and open-source data engineering tools such as ElasticSearch and NiFi 

• Data engineering certification such as Palantir Foundry Data Engineer, Azure Data Engineer Associate, Google Professional Data Engineer, IBM Certified Data Engineer, or similar 

 Security Clearance:  

• Active Top Secret or TS/SCI or TS/SCI with polygraph clearance

 #LI-DataAI

The work:

If you’ve ever wanted to bring true product thinking and commercial data engineering practices into government, this is the role. We’re hiring for a Sr. Data Engineer to join our Civilian portfolio at Accenture Federal Services, where our teams are building modern digital products that directly improve everyday experiences for the public.
 
As a Sr. Data Engineer, you will play a pivotal role in building a robust data platform (in Databricks) to be used by skilled data professionals analyzing and improving a highly visible online product. What makes this opportunity stand out is the client: mission-driven, product-oriented, and moving with a speed and mindset you’d expect from a Silicon Valley product company.
 
Note: The role can be remote or in-person in D.C., but U.S. citizenship is required. Databricks experience is ++

Key Responsibilities:

• Architecting and building scalable data platforms in AWS and Databricks
• Designing and implementing robust data pipelines, optimizing data infrastructure, and enhancing data feeds to improve quality, availability, and scalability
• Collaborating in a small, interactive scrum team of highly skilled data professionals to deliver in agile environment

Here's what you need: 

• 5+ years designing and implementing robust data pipelines, optimizing data infrastructure, and enhancing data feeds
• Experience with ETL and API data interfaces
• Experience with Open-source technologies and data streaming in Apache Kafka
• Prior design and implementation of Medallian Data Architecture
• Strong communication skills and ability to work in fast-paced, collaborative team
• Must be a US Citizen, eligible for Public Trust clearance

Preferred experience:

• Extensive engineering experience in Databricks Platforms

As the Data Engineer Team Lead, you will lead a team of talented engineers responsible for building and maintaining the data lifeblood.  You will provide the technical vision and hands-on leadership for the design, development, and sustainment of all data pipelines. This senior role requires you to champion innovation through governance, driving the adoption of reusable templates, automation, and modern data engineering practices to deliver resilient, scalable, and cost-efficient data solutions for the DoD.

Responsibilities:

• Lead, mentor, and manage a team of data engineers working on new pipeline development and operations & maintenance (O&M).
• Drive the technical strategy for the data pipeline ecosystem, ensuring stability, scalability, and efficiency.
• Enforce the use of reusable pipeline templates, automated monitoring patterns, and Infrastructure-as-Code (IaC) deployment standards established by the architecture team.
• Oversee the development of new data pipelines using modern, modular patterns like Databricks Delta Live Tables.
• Direct the optimization of existing pipelines through the implementation of automated monitoring, alerting, and proactive schema drift detection.
• Facilitate code reviews, enforce documentation standards, and ensure the team adheres to agile best practices.
• Collaborate with the Solution Architect to identify and implement technical improvements, such as leveraging GPUs for large-scale transformations.

Must have: 

• 10+ years of experience in data engineering or software engineering
• Expert-level proficiency with Python, SQL, Spark, or PySpark
• Deep experience with cloud data platforms (e.g., AWS or Azure) and data engineering platforms like Databricks, Palantir, or Snowflake
• Demonstrated experience leading projects
• US Citizenship (No Dual Citizenship)

Nice to have: 

• Experience working in high-security DoD environments (e.g., SIPR, JWICS)
• Hands-on experience with Databricks Delta Live Tables, Terraform for IaC, and CI/CD pipelines
• Familiarity with data orchestration tools (e.g., Airflow) and data quality frameworks (e.g., Great Expectations)
• Experience with streaming data technologies (e.g., Kafka) and containerization (Docker, Kubernetes)
• Extensive experience with the development and maintenance of scalable ETL/ELT tools and services

Security Clearance:

• Active Secret or TS or TS/SCI clearance

As the Data Governance Lead, you will serve as the strategic and operational leader responsible for establishing and maturing the organization's data governance framework . You will define the "rules of the road" for the program's data assets, ensuring they are managed in a consistent, secure, and high-quality manner. This role is a critical link between business, security, and technology stakeholders, requiring you to lead through influence and build a culture where data is treated as a strategic asset. You will lead a team of governance and catalog specialists to implement policies, stand up a data stewardship program, and drive the adoption of the enterprise data catalog as the single source of truth for metadata.

Responsibilities:

• Develop, implement, and manage the enterprise-wide data governance strategy, framework, and policies
• Lead and mentor a team of data governance professionals and data catalog administrators
• Establish and facilitate a Data Stewardship Council, composed of data owners and stewards from across the organization, to drive accountability for data assets
• Oversee the strategy and operation of the enterprise data catalog (e.g., Collibra), ensuring it effectively supports data discovery, lineage, and governance objectives
• Define and enforce standards for data quality, data definitions, and metadata management; oversee processes for issue resolution and data validation
• Partner with legal, security, and compliance teams to ensure data governance policies align with regulatory and security requirements
• Develop and monitor key performance indicators (KPIs) to measure the effectiveness of the data governance program and report progress to senior leadership
• Champion data literacy and the value of data governance across the organization through training and communication initiatives

Must have: 

• 8+ years of experience in data management, with at least 4+ years in a dedicated data governance role
• 3+ years of experience in a leadership or management capacity, leading teams and/or large-scale programs
• Deep expertise in designing and implementing data governance frameworks, policies, and standards
• Hands-on experience with enterprise data governance and cataloging tools such as Collibra, Alation, or Informatica Axon
• Proven ability to lead cross-functional initiatives and manage senior stakeholders
• Strong understanding of metadata management, data quality, and data stewardship principles
• US Citizenship (No Dual Citizenship)

Nive to have: 

• Certified Data Management Professional (CDMP) or similar certification
• Experience implementing a data governance program 
• In-depth knowledge of data security and compliance regulations relevant to the public sector
• Excellent communication and change management skills

Security Clearance:

• Active TS or TS/SCI clearance

Job Description:

The Palantir Data Engineer leverages advanced Python skills within a small team to develop and implement data transformation pipelines in Palantir's environment. The Data Engineer will also integrate with external systems via API, parse API responses into usable data objects, design user interfaces, and develop custom functions with TypeScript. Data Engineer will conduct code reviews, solution brainstorming, and define UI designs and functionalities.

Work you'll do:

• Movement of structure and unstructured data using approved methods.
• Execute data ingestion activities for storing data in a local or enterprise level location.
• Develop code to format data that supports exploration.
• Analyze source data formats and work with Data Scientists and partners to determine the formats and transforms that best meet mission objectives.
• Develop code and tools to provide one-time and on-going data extraction from various repositories, formatting and transformations into enterprise or standalone data models.
• Develop new ETL and perform O&M and enhancements on existing ETL code using best practices/standards.
• Develop and deliver documentation for each project including ETL mappings, code use guide, code location, and access instructions.
• Perform tier 2 level triage with customers and translate concerns into specific requirements.
• Develop new tools, code, and services to execute data engineering activities involving data of varying types and in varying conditions. 

Here’s what you’ll need:

• 4 to 7+ years of experience with all of the following:
  • Python
  • TypeScript
  • Development and maintenance of extract, transform and load (ETL) tools and services
  • Cloud and on-prem data storage and processing solutions
  • Python, SQL, Spark and other data engineering programming
  • COTS and open-source data engineering tools such as ElasticSearch and NiFi Agile / Scrum

Bonus points if you have:

• Palantir Foundry
• Palantir Pipeline Builder
• Palantir Workshop

Security clearance:

• Active TS/SCI with Poly clearance is required

The work: 

Key Responsibilities:

Job Description

As a Data Engineer at the Senior Analyst level, you will be a key contributor to the team responsible for building and maintaining the data pipelines for a data platform. This is a hands-on role where you will support the development, deployment, and operation of critical data infrastructure. You will work closely with senior engineers, applying your technical skills to execute tasks, troubleshoot issues, and learn the foundations of enterprise-scale data engineering in a mission-critical environment.

Responsibilities:

• Assist in the development and maintenance of ETL/ELT data pipelines using established patterns and tools.
• Utilize reusable pipeline templates and Infrastructure-as-Code (IaC) scripts to deploy data flows consistently and efficiently.
• Support the O&M of existing pipelines by monitoring performance, troubleshooting failures, and responding to alerts.
• Execute data quality checks and assist in the implementation of data validation rules using frameworks like Great Expectations.
• Work with senior team members to test and deploy new pipeline features and optimizations.
• Contribute to the creation and maintenance of technical documentation for data pipelines and processes.

Must have:

• 2+ years of experience in a data-focused role (e.g., data engineering, backend development, database administration).
• Experience with Python and SQL for data manipulation and scripting.
• Familiarity with data engineering concepts, including ETL processes and data warehousing.
• Exposure to cloud environments (e.g., AWS, Azure) and data platforms like Databricks or Snowflake.
• Basic understanding of Agile/Scrum methodologies.
• A strong desire to learn and grow in the data engineering field.
• US Citizenship

Nice to have:

• Experience with Spark/PySpark.
• Familiarity with Infrastructure-as-Code tools like Terraform.
• Exposure to data orchestration tools (e.g., Airflow) or CI/CD pipelines.
• Experience working in a DoD or government environment.

Security Clearance:

• Active TS or TS/SCI clearance

The Work:

We are seeking a motivated Mid Engineer to support the development of a document scanning and classification platform leveraging Microsoft 365 and AI technologies. This role will assist in building and enhancing automation tools that process, analyze, and manage large volumes of documents across SharePoint and network file systems. Key Responsibilities

• Support development of Python-based tools for document scanning, extraction, and processing
• Assist in automating workflows using PowerShell and Microsoft 365 services
• Work with SharePoint Online libraries, metadata, and document structures
• Contribute to data migration activities from file shares to SharePoint Online
• Help implement and test document classification and records management processes
• Analyze file metadata and content to support categorization and compliance efforts
• Collaborate with senior engineers on integrating AI services (e.g., Azure OpenAI)
• Perform testing, validation, and troubleshooting of automation pipelines
• Document scripts, processes, and technical configurations

Here’s What You Need:

• 3 -5 years of experience
• Experience with Python scripting
• Experience with PowerShell scripting
• Understanding of SharePoint Online and Microsoft 365 ecosystem
• Exposure to data handling, file systems, or data migration concepts
• Strong analytical and problem-solving skills Preferred Skills
• Knowledge of records management or information governance concepts
• Exposure to Azure services or cloud-based tools
• Experience working with structured and unstructured data Profile
• Willingness to learn and grow in AI-enabled solutions
• Strong attention to detail and ability to work with large datasets

Eligibility Requirements:

US – Citizen

TS or Q clearance

Accenture Federal Services is seeking a Data Platform Engineer to join our secure cloud platform team supporting government customers at Hill Air Force Base. This role is execution-focused with strong data platform engineering depth — you will design, build, and operate the streaming and batch data pipelines, lakehouse patterns, and platform services that enable rapid, secure delivery across a complex government program. The ideal candidate brings hands-on GitOps and infrastructure-as-code expertise, is comfortable in classified multi-network environments, and embodies extreme ownership. 

What Success looks like:

• Data pipelines are reliable, automated, and instrumented with observability and quality gates. 
• Platform services (Kafka, Airflow, Spark, EMR/Glue/Redshift) are standardized and version-controlled. 
• Infrastructure is defined as code and operated through GitOps — no snowflake systems. 
• Security and compliance controls are embedded into pipelines and platform services. 
• You operate with minimal supervision and proactively close gaps. 

What you’ll do:

• DevOps & Platform Engineering

• Design, implement, and maintain CI/CD for data pipelines and platform services
• Build and manage IaC using Terraform, Ansible, and AWS CDK
• Operate tooling: Crossplane, Backstage, Argo CD
• Implement GitOps workflows using GitLab/GitHub
• Manage Kubernetes and Docker for data services

• Cloud Infrastructure & Operations

• Design secure, scalable data platform architectures on AWS GovCloud and Azure Government
• Optimize network architecture for data movement
• Manage IAM and secrets for pipelines
• Administer Linux/Windows systems with monitoring and logging
• Troubleshoot and optimize pipelines (Kafka/Spark tuning, S3/Redshift patterns)

• Security & Compliance

• Implement security controls aligned with NIST, FedRAMP, and DISA STIG
• Embed data governance: classification, lineage, retention, encryption
• Integrate automated security and policy-as-code checks
• Support audits, ATO, and compliance assessments
• Manage encryption, keys, and access in classified networks

• Collaboration & Continuous Improvement

• Operate within SAFe Agile ceremonies
• Mentor peers and drive engineering standards
• Identify optimization opportunities across platform components
• Document runbooks and operational procedures

Ideal Technical Background:

• Kafka, Airflow, Spark; AWS EMR, Glue, Redshift
• Lake/lakehouse architecture and large-scale data movement
• GitOps & IaC: Terraform, Ansible, AWS CDK
• CI/CD: GitLab/GitHub
• Kubernetes, Docker
• Crossplane, Backstage, Argo CD preferred
• Python, Bash, PowerShell; Linux/Windows
• Strong AWS experience (GovCloud preferred)

What you’ll need:

• 5 years of cloud, infrastructure, or data platform engineering experience
• 3 years of designing secure data platform architectures
• Hands-on experience with IaC and DevOps in production
• Experience in classified environments (ex: NIPR/SIPR/JWICS)
• Background in data engineering and security hardening

Bonus Points if you have:

• Bachelor’s degree
• AWS or Azure certifications
• Security+ or equivalent
• CKA/CKAD
• CISSP or advanced security certifications
• Agile/Scrum certifications
• Familiarity with accreditation frameworks
• Data modeling and warehouse design (Redshift or equivalent)
• Streaming patterns and stateful processing
• Data catalog and lineage tooling
• GPU-accelerated data processing (CUDA/cuDNN) as a plus
• Multi-cloud architecture and advanced networking
• Configuration management (Ansible/Chef/Puppet)

Clearance:
Must have an active Top Secret level clearance

As the Automation Lead, you will be at the heart of driving efficiency and innovation across a data platform. You will lead a specialized team responsible for building the core automation frameworks, CI/CD pipelines, and reusable patterns that all other engineering teams will leverage. This is a hands-on leadership role where you will not only set the technical strategy for automation but also contribute directly to the development of foundational tools. Your mission is to eliminate manual toil, enforce quality, and accelerate the delivery of mission-critical data capabilities.

Responsibilities:

• Lead, mentor, and manage a team of automation engineers, fostering a culture of innovation and excellence.
• Design, build, and maintain robust, scalable CI/CD pipelines for data engineering, software, and MLOps workflows.
• Develop and own the strategy for Infrastructure-as-Code (IaC), creating and managing a library of reusable Terraform modules for consistent environment provisioning.
• Architect and implement automated solutions for testing, monitoring, and alerting to ensure the reliability of our data platforms and pipelines.
• Champion automation best practices across all engineering teams, providing guidance and developing templates to ensure adoption.
• Collaborate closely with Data Engineering, Data Products, and AI/ML teams to understand their needs and deliver automation solutions that accelerate their work.
• Evaluate, prototype, and recommend new automation technologies and tools to continuously improve our development and operational capabilities.
• Script and automate complex, repetitive tasks to improve team efficiency and reduce the potential for human error.

Must have: 

• 5+ years of experience in DevOps, Site Reliability Engineering (SRE), or automation-focused software/data engineering.
• At least 2 years of experience in a technical leadership, team lead, or mentorship capacity.
• Expert-level, hands-on experience with Infrastructure-as-Code (IaC) tools, particularly Terraform.
• Deep expertise in designing and implementing CI/CD pipelines using tools like GitLab CI, Jenkins, or GitHub Actions.
• Strong scripting and programming skills, with expert proficiency in Python.
• Proven experience working in a cloud environment (AWS, Azure). 
• US Citizenship (No Dual Citizenship).

Nice to have:

• Experience building automation specifically for data platforms like Databricks or Snowflake.
• Familiarity with MLOps principles and tools (e.g., MLflow, Kubeflow).
• Experience with containerization and orchestration technologies (Docker, Kubernetes).
• Experience working in a high-security DoD or Intelligence Community environment.

Security Clearance:

• Active TS or TS/SCI clearance

As a Sr. Cloud Data Engineer, you’ll work with team members to build, deploy, and operate data pipelines and data engineering components to enable data brokering and exchange capabilities across a diverse range of producers and consumers.

Responsibilities:

In this role, you will be responsible for building robust, scalable data pipelines while working collaboratively with cross-functional teams to ensure seamless integration, optimized performance, and efficient delivery of solutions.

• Work with team members to operationalize data pipelines and supporting cloud infrastructure
• Collaborate with external data producers and consumers to obtain and provide data through interfaces such as REST APIs and S3
• Provide day-to-day support of deploying Python-native data pipelines and performing data engineering tasks to enable data brokering and exchange capabilities 
• Provide Tier 2/3 troubleshooting and incident resolution support for data pipelines in Production
•  

What you’ll need to succeed: 

• 4 years of proven experience in data engineering, with expertise in designing, developing, and maintaining data ingestion, transformation, and loading pipelines and components
• Demonstrated experience in designing and deploying data pipelines leveraging AWS cloud infrastructure across multiple classification domains (e.g., IL5 to IL6+)
• Experience with Infrastructure-as-Code (IaC) tools, including Terraform, CloudFormation, or Ansible, to automate deployment of data pipeline cloud infrastructure
• Understanding of RMF security principles and hands-on experience implementing security controls for data pipelines in cloud environments
• Strong scripting and programming skills in languages such as Go, Python, and Bash
• Experience with data pipeline tools and technologies such as Nifi, Hadoop, HDFS, and Kafka.

Nice to have:

• Experience implementing data pipelines in the Cloudera Data Platform environment is highly preferred.
• Strong communication skills, with the ability to clearly convey complex technical concepts

Clearance:

• An active TS/SCI with polygraph is required

#clearancejobs

#LI-DataAI

As a Data Analyst on the Innovation and Automation team, you will play a crucial role in using data to improve our own engineering and operational processes. Unlike a typical data analyst who supports a business unit, your "customers" are our internal engineering and development teams. You will work under the guidance of senior team members to gather, analyze, and visualize data from our development lifecycle tools. Your work will help identify bottlenecks, measure the success of automation initiatives, and provide the insights that make our technical teams more efficient. This is a hands-on role for an analyst who is eager to apply their skills to the world of DevOps, DataOps, and process improvement.

Responsibilities:

• Query and analyze data from various sources, including CI/CD systems (e.g., GitLab), project management tools (e.g., Jira), and application logs, to support automation initiatives
• Build and maintain dashboards and reports in tools like Tableau or Power BI to track key engineering metrics such as pipeline success rates, deployment frequency, and cycle times
• Support senior analysts and leads by providing data and analysis to help quantify the impact of automation projects (e.g., time saved, errors reduced)
• Assist in identifying trends and patterns in operational data that may indicate opportunities for process improvement or automation
• Help prepare and present findings to the team, translating data into clear visualizations and summaries
• Document your analytical processes and data sources to ensure repeatability and clarity

Required Qualifications:

• 2+ years of experience in a data analyst or similar role
• Strong proficiency in SQL for querying and data manipulation
• Experience with Python or R for data cleaning and analysis
• Proficiency with a data visualization tool such as Tableau or Power BI
• A strong analytical mindset and the ability to work through complex data problems

Preferred Qualifications:

• A strong desire to learn about DevOps, automation, and software development lifecycle best practices
• Familiarity with analyzing metrics from software development tools like Jira or GitLab
• Basic understanding of cloud environments (AWS, Azure)
• Experience working in a high-security DoD or Intelligence Community environment
• Good communication skills and the ability to work collaboratively within a technical team

Security Clearance:

• Active TS or TS/SCI clearance

As a Data Engineer Specialist on the Innovation and Automation team, you will serve as a subject matter expert, blending deep data engineering expertise with a passion for automation. You will not build individual data pipelines for business users; instead, you will build the factory that produces them. Your mission is to design, develop, and implement the reusable frameworks, automated patterns, and core tooling that our data engineering teams will use to build their own pipelines faster, more reliably, and more consistently. This is a highly technical, hands-on role for a problem-solver who wants to act as a force multiplier for the entire data organization.

Responsibilities:

• Act as a technical expert on the design and implementation of automated data engineering solutions
• Develop and maintain a library of standardized, reusable ETL/ELT pipeline templates using Python, SQL, and frameworks like Databricks or Snowflake
• Engineer and implement robust, automated data quality and testing frameworks (e.g., using tools like Great Expectations) that are embedded within the core pipeline templates
• Contribute to the development of Infrastructure-as-Code (IaC) modules (Terraform) for the automated provisioning of data infrastructure
• Enhance and optimize the CI/CD for Data (DataOps) pipelines, ensuring seamless and reliable deployment of data workflows
• Serve as an escalation point for the most complex data engineering and automation challenges, providing expert-level troubleshooting and guidance to other engineers
• Mentor other data engineers on automation best practices, code standards, and the use of the frameworks you build
• Research and prototype cutting-edge data engineering and automation technologies to drive continuous improvement

Must have: 

• 5+ years of hands-on experience in data engineering
• Expert-level programming skills in Python and advanced SQL
• Proven, in-depth experience building and optimizing data pipelines in a cloud environment (AWS, Azure) on platforms like Databricks or Snowflake
• Strong, hands-on experience with Infrastructure-as-Code (IaC) using Terraform
• Demonstrable experience with CI/CD principles and tools (e.g., GitLab CI, Jenkins, GitHub Actions) applied to data workflows
• Deep understanding of modern data architecture, data modeling, and software engineering best practices

Nice to have:

• Experience in a DevOps or Site Reliability Engineering (SRE) role
• Direct experience developing and operationalizing a "pipeline factory" or similar framework
• Familiarity with data orchestration tools (e.g., Airflow) and containerization (Docker, Kubernetes)
• Experience working in a high-security DoD or Intelligence Community environment
• Proven ability to diagnose and resolve complex performance, data quality, and system-level issues

Security Clearance:

• Active TS or TS/SCI clearance

We are seeking a seasoned Data Strategy and Governance Lead to work with a government organization to establish a modern, secure, and effective data management framework. The ideal candidate will be an expert in data policy, strategy, and governance, with a proven track record of guiding organizations from on-premise data environments to secure hybrid-cloud models.

This role is a strategic advisory position focused on developing the policies, strategies, and governance plans necessary to manage the organization's data as a strategic asset. The ability to generate detailed data, architecture, and technical design artifacts is essential to enable engineering changes of the candidate’s identified strategy.

Responsibilities

• Develop and implement a comprehensive data governance framework, including policies for data quality, stewardship, security, and lifecycle management.
• Create a long-term data strategy that aligns with the organization's mission, with a special focus on the transition to a secure hybrid-cloud environment.
• Embed a "zero-trust" security model into all data policies and strategies to ensure the highest level of security.
• Design and implement a data governance model that defines clear roles, responsibilities, and accountability for data assets across the organization.
• Lead exercises to create a complete inventory of the organization's data assets to identify what data exists and where it is located.
• Conduct a thorough analysis of current access policies and management systems, identifying inconsistencies and areas for improvement.
• Define the target "to-be" state for data management, outlining how data will be stored, accessed, and governed in a modernized environment.
• Develop a strategic roadmap with clear milestones to guide the organization's transition to its desired future state for data management.
• Create logical and physical data models to visualize how data is being created, collected, stored, and accessed. 

Qualifications

• 6 years of experience in data management, with at least 3 years in a leadership role focused on data strategy, governance, and policy.
• Proven experience working with government organizations and a deep understanding of the unique challenges and regulatory requirements of the public sector.
• Extensive knowledge of cloud technologies (such as any of the following: AWS, Azure, GCP) and experience guiding organizations through the transition from on-premise to secure hybrid-cloud environments.
• Experience in establishing and running data governance programs, including the development of policies, standards, and processes.

Nice to have

• Strong understanding of modern cybersecurity principles, with specific experience implementing "zero-trust" security architectures.
• Excellent communication and stakeholder management skills, with the ability to articulate complex data concepts to both technical and non-technical audiences.

Clearance

• An active Top Secret with SCI eligibility and willing to obtain polygraph

#clearancejobs

#LI-Cyber 

As a senior Data Engineer, you will be a key technical contributor on the team building and maintaining the critical data pipelines for a data platform. You will apply your deep expertise to design, develop, and optimize robust ETL/ELT processes that move and transform data for DoD-wide use. In this role, you will not only build solutions but also mentor junior engineers and help drive the adoption of modern data engineering practices and automation.

Responsibilities:

• Design, build, and maintain scalable and resilient data pipelines for both new data sources and existing systems within the data platform ecosystem.
• Implement and optimize pipelines using modular patterns, such as Databricks Delta Live Tables, following governance from the architecture team.
• Develop and integrate automated monitoring, alerting, and data quality checks into every pipeline to reduce downtime and ensure data integrity.
• Utilize Infrastructure-as-Code (IaC) with tools like Terraform to create consistent, repeatable deployments and CI/CD processes.
• Analyze complex source data formats and collaborate with data scientists and stakeholders to design transformations that meet mission objectives.
• Participate in and lead code reviews, enforce best practices, and mentor junior data engineers.
• Troubleshoot and resolve complex issues with data pipelines, and contribute to the ongoing improvement of O&M processes.

You are: 

• 3 years of experience in data engineering
• Strong experience with the development and maintenance of extract, transform, and load (ETL) tools and services
• Proficiency in Python, SQL, Spark, or PySpark
• Hands-on experience with cloud environments (AWS or Azure) and data platforms like Databricks, Palantir, or Snowflake
• Experience working in an Agile/Scrum development environment

Nice to have: 

• Experience working in high-security DoD environments (e.g., SIPR, JWICS)
• Hands-on experience with Databricks Delta Live Tables and Terraform
• Experience with containerization technologies like Docker or Kubernetes
• Knowledge of COTS and open-source data engineering tools such as NiFi or ElasticSearch

Security Clearance:

• Active TS Clearance or TS/SCI Clearance

As the Data Analyst Associate Manager, you will lead a team of analysts dedicated to bringing our data governance strategy to life. You will act as a critical link between the strategic vision set by governance leadership and the day-to-day execution required to maintain a healthy data ecosystem. Your role is to manage and mentor a team that serves as the analytical engine for the governance program, using the enterprise data catalog as its central hub. You will be hands-on, guiding your team in analyzing metadata, measuring data quality, and building the reports that provide transparency into the health and value of our data assets.

Responsibilities:

• Lead, mentor, and manage a team of data governance analysts, overseeing their daily tasks and professional development
• Oversee the day-to-day operational health of the enterprise data catalog (e.g., Collibra), ensuring metadata is being populated accurately and is useful for end-users
• Design and implement data quality monitoring processes; guide the team in analyzing data quality issues and tracking remediation efforts with data stewards
• Direct the development of dashboards and reports in tools like Tableau or Power BI to track key data governance metrics, such as data quality scores, catalog usage, and stewardship activity
• Partner with data stewards across the organization to facilitate the definition of business terms, certification of data assets, and documentation of data lineage within the catalog
• Act as a subject matter expert on the data catalog, training users and championing its adoption as the single source for data discovery
• Translate high-level data governance objectives into specific analytical projects and tasks for your team
• Report on the status of data quality and governance initiatives to the Data Governance Lead and other stakeholders

Must have:

• 5+ years of experience in data analysis, data governance, advisory or data management
• 1+ years of experience in a formal or informal leadership capacity (e.g., team lead, project lead, mentoring junior analysts)
• Experience creating reports and dashboards with a data visualization tool like Tableau or Power BI
• Strong understanding of data governance principles

Nice to have:

• Strong proficiency in SQL for data analysis and validation
• Hands-on experience with an enterprise data catalog or governance tool (e.g., Collibra, Alation, Informatica Axon)
• Experience managing or administering a data catalog tool
• Experience working directly with business data stewards to define and document data
• Familiarity with data modeling concepts
• Excellent project management and communication skills

Security Clearance:

• Active Secret or TS or TS/SCI clearance