Job Description
Job Description
Job Title : Cloud Data Engineer
Location : Remote (occasional travel to the Washington D.C. metro area may be required)
Clearance Required : Public Trust
Position Overview
We are seeking a customer-focused Cloud Data Engineer to join a dynamic team of subject matter experts and developers. This role involves designing and implementing full lifecycle data pipeline services for Azure-based data lake, SQL, and NoSQL data stores. The ideal candidate will be mission-driven, delivery-oriented, and skilled in translating business requirements into scalable data engineering solutions.
Key Responsibilities
- Maintain and operate legacy ETL processes using Microsoft SSIS, PowerShell, SQL procedures, SSAS, and .NET.
- Develop and manage full lifecycle Azure cloud-native data pipelines.
- Collaborate with stakeholders to understand data requirements and deliver effective solutions.
- Design and implement data models and pipelines for various data architectures including relational, dimensional, lakehouse (medallion), warehouse, and mart.
- Utilize Azure services such as Data Factory, Synapse Pipelines, Apache Spark Notebooks, Python, and SQL.
- Migrate existing SSIS ETL scripts to Azure Data Factory and Synapse Pipelines.
- Prepare data for advanced analytics, visualization, reporting, and AI / ML applications.
- Ensure data integrity, quality, metadata management, and security across pipelines.
- Monitor and troubleshoot data issues to maintain performance and availability.
- Implement governance, CI / CD, and monitoring for automated platform operations.
- Participate in Agile DevOps processes and continuous learning initiatives.
- Maintain strict versioning and configuration control.
Required Qualifications
Bachelor’s degree in Computer Science or related field with 8+ years of experience, or Master’s degree with 6+ years.Minimum 4 years of experience in ETL development using Microsoft SSIS, SQL, SQL Agent, and scripting (PowerShell).Proficiency in scripting languages such as SQL, T-SQL, Python, and PySpark.Experience with Microsoft SQL Server and BI tools including SSIS, SSRS, SSAS (cubes).Hands-on experience with Azure cloud services including Data Lake, Synapse, and Data Factory.Strong understanding of data engineering principles and cloud-native architectures.Preferred SkillsExperience with data lakehouse architecture and medallion design.Familiarity with Agile methodologies and DevOps practices.Knowledge of data governance and security best practices.