Sr Data Engineer, AI

Constellation Energy Generation, LLC. is seeking a senior data engineer to help lead the design, build, test, implement, and maintain AI solutions, products, and processes in an Azure-based environment. This role partners with cross-functional teams in an agile setting, focusing on secure, maintainable engineering practices while owning AI data platform and pipeline delivery.

This position is based in Baltimore, MD and is an onsite opportunity. The role offers a salary range of USD 129,600 - 194,400 per year, with a structured total rewards package that includes comprehensive benefits and bonus and 401(k) components.

What you’ll do

• Lead activities spanning design, build, testing, implementation, and maintenance of AI solutions, products, and processes.
• Evaluate technology standards and product availability, weighing risks and benefits to deliver solutions aligned to business and IT needs.
• Coordinate tasks for less experienced engineers and collaborate across teams as required.
• Partner with scrum masters, project managers, QA, Creative, and UX to support compliance with project needs.
• Architect, design, implement, and test systems to support high-quality releases.
• Review peer code, advocate for standard development methodologies, and support an inclusive, highly cross-functional team environment.
• Maintain deep technical knowledge across business areas and share knowledge through seminars, presentations, and publications within IT and Constellation.
• Participate in technological innovation to drive business opportunities and solve complex problems.
• Coach and provide oversight to engineers assigned to product or project teams.
• Ensure secure, maintainable code and configurations, and support deployments using Azure DevOps.
• Support issue investigation across application layers and databases, using strong debugging and problem-solving skills.
• Identify opportunities to improve and scale Azure architecture, and shape core team processes to improve operational efficiency and quality.
• Design and query database tables, views, functions, stored procedures, and batch processes.
• Develop, implement, and support interfaces connecting websites, back-end systems, and third-party cloud solutions, vendors, and customers.
• Engage with business partners to gather information, analyze requirements, and deliver practical, efficient, cost-effective solutions.
• Design, develop, and review complex code or configurations to ensure AI solutions meet functional and technical specifications.
• Write product specifications and design documentation for assigned system components.
• Design and build large-scale AI data platforms/products & frameworks for real-time and batch processing used across the organization.
• Develop complex data algorithms for AI/ML, data analytics, machine learning, and scientific computing.
• Support proactive handling of emerging threats using indicators, and lead peer code reviews.
• Apply version control principles (for example, Git) while working in an agile environment.
• Assist with white papers and presentations to explain technology recommendations to IT stakeholders.
• Implement data governance frameworks to ensure and manage data quality.

Key experience & qualifications

• 3+ years of experience.
• Bachelor’s degree in Accounting (or 5-years experience in lieu of degree; 9-years experience in lieu of degree per the stated equivalency).
• Experience with private and public cloud architectures, including pros/cons and migration considerations.
• 5-years of RDBMS experience.
• Experience with JSON, JSON-LD, and XML data structures.
• Experience implementing data pipelines using latest technologies and techniques.
• Experience with Azure DevOps and tools such as Copado, GitHub, Heroku, ServiceNow, or similar.
• 3+ years hands-on programming experience with languages such as Java 8, C#, node.js, Python, SQL, and Unix shell/Perl scripting.
• 5+ years of industry experience as a data engineer, including involvement in the data component of the AI/ML lifecycle and applied machine learning topics.
• 3+ years of consulting or client service delivery experience on Azure.
• Experience handling structured and unstructured datasets; strong t-SQL skills with experience in Azure SQL DW.
• Experience with data modeling and advanced SQL techniques.
• Cloud migration methodologies using tools such as Azure Data Factory and Event Hub (and related services mentioned in the listing).
• Knowledge of ETL tools and ETL/ELT pipelines.
• Advanced hands-on experience with Databricks and Spark (PySpark preferred), building and optimizing workflows and pipelines.
• Hands-on proficiency with Python and PySpark for ETL/ELT pipeline development and support.
• Experience configuring secure external data connections (examples include Azure Data Lake Storage and on-prem SQL Server) using Service Principals, SAS Tokens, OAuth, and mounting techniques.
• Strong understanding of data security, encryption, and compliance standards, plus data governance frameworks.
• Proven expertise with Azure Data Factory (ADF) for orchestrating and automating data workflows across cloud and on-premises environments.

Benefits

• Eligible employees are offered a bonus program.
• 401(k) with company match.
• Employee stock purchase program.
• Comprehensive medical, dental, and vision benefits, including robust wellbeing programs.
• Disability and life insurance benefits.
• Paid time off for vacation, holidays, and sick days.
• Comprehensive benefits package that includes bonus and 401(k).

Total rewards

• Expected salary range of $145,800 to $162,000, varying based on experience, along with a comprehensive benefits package that includes bonus and 401(k).

Technologies: AI, Azure, Azure DevOps, Azure SQL DW, t-SQL, SQL, RDBMS, JSON, JSON-LD, XML, Java 8, C#, node.js, Python, Unix shell/Perl scripting, Git, GitHub, Copado, Heroku, ServiceNow, Azure Functions, Event Grids, Service Bus Queues, Cosmos DB, Azure Data Factory, Event Hub, Azure Data Lake Storage, Databricks, Spark, PySpark, ETL/ELT pipelines, ETL tools, Event driven architecture, AWS, GCP, OAuth, SAS Tokens, Service Principals, On-prem SQL Server.