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Arlington, Virginia, United States
Remote only
When you join AIS, you’re joining a mission-driven team that’s passionate about making a difference. You’ll work on projects that matter, alongside industry-leading experts, in an environment that fosters innovation, driving client success, and empowering our team to make a lasting impact. As an employee-owned company, we value collaboration, inclusivity, continuous growth, and shared success.
Employee Ownership: Your contributions directly impact the company’s success, and you share in its achievements.
Continuous Learning: Access to resources, training, and mentorship to support your professional growth.
Inclusive Culture: A workplace where diversity is celebrated, and everyone’s voice is valued.
Mission-Driven Work: Engage in projects that make a meaningful difference for our clients and communities.
At AIS, we're looking for more than just skills - we're looking for driven individuals who are passionate about making a difference, eager to grow, and aligned with our core principles.
Core Knowledge & Skills: Develops strong skills in building and maintaining data pipelines using industry-standard tools and platforms. Gains proficiency in scripting languages (such as Python, Shell, SQL), cloud data services, and analytics platforms. Understands data warehousing concepts and best practices for data security and compliance.
Work & Complexity: Manages and optimizes data pipelines with multiple sources and destinations, ensuring data integrity and timeliness. Troubleshoots and resolves data issues, automates repetitive tasks, and contributes to workflow efficiency.
Quality & Independence: Delivers high-quality, maintainable, and well-documented code. Maintains rigorous standards for data accuracy and reliability, and ensures compliance with internal policies and regulations. Operates with growing autonomy and takes initiative to improve data processes.
Teamwork & Communication: Collaborates closely with data scientists, analysts, and stakeholders to understand and meet data needs. Integrates into cross-functional teams, mentors junior team members, and actively participates in feedback and knowledge sharing.
Consulting & Engagement: Provides consulting services to internal teams on data operations best practices. Identifies opportunities for process improvements, acts as a technical advisor on projects, and supports team members in adopting new tools and techniques.
As a Data Engineer, you will design, build, and operate scalable data platforms and products within modern cloud environments—primarily Microsoft Azure, with Databricks as a key analytics and processing technology. You will work closely with analytics, data science, and business teams to enable reliable, governed, and high‑quality data for reporting, analytics, and advanced use cases.
Key responsibilities include:
Design, build, and maintain scalable batch and near‑real‑time data pipelines using cloud‑native services
Develop and optimize data ingestion, transformation, and orchestration workflows across diverse data sources
Build and maintain ELT/ETL frameworks to support analytics, reporting, and data science use cases
Prepare, transform, and curate raw data into analytics‑ready datasets for both technical and non‑technical stakeholders
Develop, deploy, and operate data products within Azure‑based analytics platforms (e.g., Databricks, Synapse, Fabric)
Implement data quality checks, monitoring, and observability to ensure data accuracy, reliability, and integrity
Apply data governance, security, and privacy controls aligned with enterprise and regulatory standards
Monitor data platform performance and proactively implement cost and performance optimizations
Partner with data scientists, analysts, and analytics engineers to ensure trusted and timely access to data
Design data solutions that are scalable, reusable, automated, and well‑governed by default
This is a remote position
Bachelor’s degree (or equivalent experience) in Computer Science, Information Systems, Engineering, Mathematics, Statistics, or a related field
Experience working within a modern cloud data platform, with Microsoft Azure strongly preferred
Hands‑on experience with Apache Spark or other distributed data processing frameworks
Strong SQL skills and experience with relational data modeling and query optimization
Proficiency in Python, with experience building data pipelines or transformations (PySpark experience a plus)
Experience with data orchestration and workflow tools (e.g., Azure Data Factory, Airflow, or similar)
Solid understanding of data modeling, schema design, and analytical data structures
Familiarity with data governance, security, and quality concepts in enterprise environments
Strong problem‑solving, communication, and collaboration skills
Ability to work independently while contributing effectively within cross‑functional teams
Preferred Qualifications
Experience with Databricks (Databricks SQL, Delta Lake, Lakehouse patterns)
Experience with Azure analytics services such as Synapse Analytics, Fabric, Azure Data Factory, or Azure Data Lake
Exposure to data ingestion and integration tools (e.g., Fivetran, Matillion, Airbyte)
Understanding of CI/CD practices and infrastructure‑as‑code in data environments
Experience supporting analytics and BI tools (e.g., Power BI)
Applied Information Sciences does not discriminate on the basis of race, national origin, religion, color, gender, sexual orientation, age, disability, protected veteran status, or any other basis. Employment decisions are based solely on qualifications, merit, and business needs.
