Data Engineer

AIS (Applied Information Sciences) is a mission-driven company that values collaboration and innovation. They are seeking a Data Engineer to design, build, and operate scalable data platforms primarily in Microsoft Azure, ensuring high-quality data for analytics and reporting.

Responsibilities:

• 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

Requirements:

• 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
• 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)