Software Development III

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.

Requirements

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 Skills

• Experience with data lakehouse architecture and medallion design.
• Familiarity with Agile methodologies and DevOps practices.
• Knowledge of data governance and security best practices.

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