Senior DataOps Engineer

About the role

Voyager is an innovative space, defense, and national security technology company committed to advancing and delivering transformative, mission-critical solutions. We tackle the most complex challenges to unlock new frontiers for human progress, fortify national security, and protect critical assets to lead in the race for technological and operational superiority from ground to space.

Forge the Future: Join Voyager Technologies

The future belongs to those who build it. At Voyager Technologies, we’re building technologies that protect lives, expand frontiers and prepare us for what’s next. And we’re doing that with people who are wired to solve, build, adapt and lead. These roles are not for the faint of heart.

You’ll help lay the foundation for humanity's future. Join a culture where innovation thrives, curiosity is rewarded, and impact is real. We’re a company of doers, thinkers and builders, united by purpose and grounded in reality.

If you want to put your skills to work where the stakes are real and the mission is bigger than any one person,  forge the future with Voyager.

Job Summary

The DataOps Engineer is responsible for designing, building, and operationalizing data infrastructure that powers the organization's analytics and business intelligence capabilities. This role sits at the intersection of data engineering, cloud architecture, and DevOps - owning end-to-end data pipelines, platform reliability, data quality, and cloud infrastructure in a regulated environment. Responsibilities span data pipeline development, cloud migrations, platform operations, and infrastructure management across multi-cloud environments.

The ideal candidate is fluent in hands on coding of Python or PowerShell, experienced with infrastructure-as-code tools (Terraform, CloudFormation, Ansible), and comfortable owning both data engineering and cloud infrastructure responsibilities in a cleared, compliance-driven environment. This is a remote position based in the US requiring the ability to obtain a US Government Clearance.

Key Responsibilities

Cloud Migration & Infrastructure

Lead the end-to-end migration of data workloads from AWS Commercial to AWS GovCloud, including S3, Glue, Redshift, IAM, VPC, Lambda, and CloudWatch.

Identify and resolve service parity gaps between commercial and GovCloud environments; validate data integrity, encryption posture, and access controls post-migration.

Set up and administer enterprise Git repositories (GitHub, Azure DevOps, or GitLab) for the data and analytics team, including branching strategy, access controls, and code review workflows.

Migrate existing scripts, pipelines, and artifacts into version-controlled repositories and enforce DataOps source control best practices across the team.

Ensure all migrated and provisioned resources comply with NIST 800-171, DFARS, CUI, and ITAR/EAR handling requirements.

Administer and optimize cloud data services across AWS GovCloud (S3, Glue, Redshift, Lambda) and Azure Government (Synapse, ADF, ADLS Gen2, Databricks).

Manage infrastructure-as-code for all data platform resources using Terraform and CloudFormation (required); Ansible preferred for configuration management.

Monitor cloud resource utilization, enforce cost governance, and implement right-sizing recommendations for data workloads.

Maintain backup, disaster recovery, and business continuity procedures for all data platform services.

Serve as Tier 3 support for complex cloud infrastructure and data incidents; perform root cause analysis and implement preventive measures.

Data Pipeline Development & Orchestration

Design, build, and maintain scalable ELT/ETL pipelines using Microsoft Fabric Data Factory, Azure Data Factory, Apache Airflow, and DBT.

Architect end-to-end data flows from ingestion through transformation to serving layers, ensuring reliability, lineage, and observability.

Implement real-time and batch data streaming using Apache Kafka, Azure Event Hubs, and Fabric Eventstream.

Automate pipeline monitoring, alerting, and self-healing mechanisms to minimize manual intervention.

Microsoft Fabric Platform Ownership

Serve as a platform engineer for Microsoft Fabric, including OneLake, Lakehouse, Warehouse, Data Factory, and Fabric Notebooks.

Design and govern OneLake architecture including workspace topology, shortcut strategy, and medallion (Bronze/Silver/Gold) layer design.

Integrate Fabric with enterprise systems including Microsoft 365 GCC High, Azure Government, Dynamics 365, and third-party data sources.

Configure Fabric capacity management, workspace permissions, and security in alignment with NIST 800-171 and DFARS requirements.

Data Architecture & Modeling

Lead the design of enterprise data models including star schema, snowflake schema, and Data Vault 2.0 patterns.

Architect Lakehouse, data warehouse, and data mesh topologies to serve analytical, operational, and reporting workloads.

Define and enforce naming conventions, semantic layer standards, and reusable data assets using Power BI semantic models and Fabric Direct Lake.

Collaborate with stakeholders to translate business requirements into scalable data architecture solutions.

DataOps Practices & CI/CD

Implement DataOps principles: automated testing, version-controlled pipelines, and continuous delivery for data assets.

Build and maintain CI/CD pipelines (Azure DevOps, GitHub Actions) for deploying data pipelines, models, and Fabric artifacts.

Write and maintain automation scripts in Python and/or PowerShell to support migration, provisioning, and operational workflows.

Containerize and orchestrate workloads using Docker and Kubernetes (AKS) for portable, scalable processing.

Data Quality & Governance

Implement data quality frameworks including automated profiling, validation rules, anomaly detection, and SLA monitoring.

Manage data lineage, metadata cataloging, and access governance using Microsoft Purview.

Enforce data classification policies for CUI, ITAR-controlled, and export-sensitive data across all pipeline stages.

Partner with compliance and cybersecurity teams to ensure data governance controls satisfy audit and regulatory requirements.

Monitoring, Troubleshooting & Support

Proactively monitor pipeline health, data freshness, and system performance using Fabric monitoring hub, Azure Monitor, and Log Analytics.

Document incident response procedures, runbooks, and architecture decisions (ADRs).

Collaboration & Documentation

Partner with data analysts, data scientists, and business stakeholders to deliver reliable data products that drive decision-making.

Create and maintain thorough documentation for pipeline design, data dictionaries, security controls, and compliance evidence.

Participate in architecture reviews, sprint planning, and cross-functional data governance committees.

Technical Skills

Cloud Platforms

AWS GovCloud: S3, Glue, Redshift, IAM, VPC, Lambda, CloudWatch - including commercial-to-GovCloud migration experience

Azure Government: ADLS Gen2, Azure Synapse Analytics, Azure Data Factory, Azure Databricks, Azure Monitor, Microsoft Purview

Compliance Configurations: NIST 800-171, DFARS, FedRAMP, CUI/ITAR/EAR handling across both cloud environments

Infrastructure as Code & Automation

Required: Terraform, AWS CloudFormation

Preferred: Ansible - configuration management and environment automation

Supporting: Bicep / ARM Templates for Azure Government resources

Scripting & Programming (Required - Python or PowerShell)

Python - pandas, PySpark, SQLAlchemy, pipeline scripting, automation

PowerShell - infrastructure automation, Azure/AWS resource management, scripting

T-SQL / Spark SQL - complex query optimization, window functions, CTEs

PySpark / Scala - distributed data processing on Databricks and Fabric Spark

KQL (Kusto Query Language) - log analytics and Fabric KQL databases

Source Control & DevOps

Git - repository setup, branching models, access management

CI/CD: Azure DevOps Pipelines, GitHub Actions, GitLab CI

Containers: Docker, Kubernetes (AKS)

Microsoft Fabric & Azure Ecosystem

Core Platform: Microsoft Fabric - OneLake, Lakehouse, Warehouse, Data Factory, Eventstream, Fabric Notebooks, KQL Database; Direct Lake mode, Fabric capacities, workspace governance

Supporting: Azure Data Lake Storage Gen2, Azure Synapse Analytics, Azure Databricks, Azure Event Hubs, Azure Monitor, Microsoft Purview; Azure Government & Microsoft 365 GCC High compliance configurations

Data Pipeline & Orchestration Tools

Apache Airflow - DAG design, dependency management, sensor patterns

dbt (data build tool) - transformation logic, testing, documentation, incremental models

Apache Kafka / Azure Event Hubs - real-time streaming architecture

Talend, Informatica - legacy ETL/ELT integration patterns

Data Architecture

Medallion architecture (Bronze / Silver / Gold Lakehouse layers)

Star schema, snowflake schema, Data Vault 2.0

Data mesh and domain-oriented data ownership patterns

Semantic layer design (Power BI semantic models, calculation groups)

Database & Storage Systems

Relational: PostgreSQL, Microsoft SQL Server, Azure SQL

NoSQL: MongoDB, Cassandra, Redis, Cosmos DB

Cloud Storage: ADLS Gen2, AWS S3, OneLake

Data Quality & Governance

Microsoft Purview - data catalog, lineage, classification, policy

Great Expectations, DBT tests - automated data quality validation

Data classification and handling for CUI, ITAR, and EAR-controlled information

If your experience aligns with our basic qualifications and you are inspired by our mission, we’d like to connect. If you don’t see the right role right now, Join Our Talent Community and stay connected as we continue to build what’s next.

Required Qualifications

Must have extensive experience leading end-to-end migration of data workloads from AWS Commercial to AWS GovCloud, including S3, Glue, Redshift, IAM, VPC, Lambda, and CloudWatch.

Must be able to demonstrate your ability to script & Program using Python or PowerShell.

Travel, Physical and/or Government Mandated Requirements:

Travel up to 10-15%, including the possibility of overnights to support customer reviews and test events

U.S. Citizenship required due to federal contract eligibility

Must have or be able to obtain and maintain an active DoD Secret Clearance

Must comply with ITAR regulations

Education & Experience

Bachelor's degree in computer science, Information Technology, Data Engineering, or a related field; or equivalent hands-on experience.

8+ years of data engineering, cloud infrastructure, or DataOps experience in a cloud-first environment.

Demonstrated hands-on experience migrating workloads to or within AWS GovCloud or Azure Government strongly preferred.

2+ years of hands-on experience with Microsoft Fabric or Azure Synapse Analytics.

Demonstrated experience in regulated environments (aerospace, defense, government contracting) with NIST 800-171 and DFARS compliance.

Proven ability to architect and deliver enterprise-grade data platforms from greenfield to production.

Soft Skills

Comfortable owning both data and infrastructure responsibilities - a generalist who can go deep when needed.

Strong ability to translate complex technical architecture into clear communication for business stakeholders.

Collaborative mindset - experienced working across data, analytics, cybersecurity, and compliance teams.

Detail-oriented with strong documentation habits in compliance-sensitive environments.

Proactive problem-solver with a continuous improvement orientation toward data reliability and platform scalability.

Preferred Qualifications-Highly desired

AWS Certi…