Overview: The Data Engineer is responsible for developing, maintaining, and supporting data pipelines using Python and SQL Server (T-SQL), while assisting with data integration from internal and external systems within a modern Azure-based data platform. The role supports critical data operations in regulated environments and provides opportunities for hands-on learning and growth under the guidance of senior data engineers. Job Description: - Develop and maintain ETL pipelines using Python and SQL Server for data ingestion, transformation, and integration from various data sources, including structured files and RESTful APIs. - Write, test, and debug Python code for data processing, automation, and basic integrations following established standards and best practices. - Create and maintain T-SQL queries, views, and stored procedures to support business logic and reporting requirements. - Assist in building and operating data workflows using Azure Data Factory, Azure SQL, and Azure Blob Storage. - Support the monitoring of data pipelines and help troubleshoot data quality issues, pipeline failures, and performance problems. - Follow defined data quality, security, and compliance procedures in regulated environments such as healthcare and financial services. - Collaborate with data analysts, software engineers, and DevOps teams to understand data requirements and upstream systems. - Participate in code reviews, implement feedback, and continuously improve coding and engineering practices. - Create and maintain clear documentation for data pipelines, logic, and operational processes. Qualifications and Experience: Education - Bachelor’s Degree — Preferred Experience - 1–4 years of professional experience in Data Engineering, Software Engineering, or a related technical role — Required - Strong hands-on proficiency in Python, including writing functions, handling errors, and debugging code — Required - Experience working with relational databases, preferably SQL Server — Required - Strong working knowledge of SQL, including joins, aggregations, subqueries, and basic performance considerations — Required - Exposure to integrating or consuming data from RESTful APIs or external data sources — Required - Familiarity with Git or similar version control systems — Required - Strong analytical and problem-solving skills with the ability to learn quickly — Required Preferred Experience - Experience with additional Azure services such as Azure Synapse, Azure DevOps, and Azure Functions - Understanding of data modeling and warehousing concepts - Exposure to cybersecurity data, SIEM tools, or SOC operations - Knowledge of .NET Framework and C#-based APIs, particularly in data consumption contexts - Background in MSP/MSSP environments or consulting - Familiarity with Power BI or other data visualization tools Knowledge, Skills, and Abilities: - Exposure to Azure data services such as Azure Data Factory, Azure SQL, or Blob Storage. - Basic understanding of ETL concepts, data validation, and pipeline monitoring. - Familiarity with data modeling fundamentals, including tables, keys, and relationships. - Awareness of data security, privacy, and compliance standards such as HIPAA and SOC2. - Experience with Power BI or other data visualization tools. - Basic understanding of application systems or APIs built using .NET or similar frameworks. - Ability to design and support scalable ETL pipelines using Python and SQL Server for data ingestion, transformation, and integration from diverse sources. - Ability to develop and optimize T-SQL stored procedures to support business logic and reporting needs. - Ability to support secure and efficient data workflows using Azure Data Factory, Azure SQL, and Azure Functions. - Ability to help ensure data quality, lineage, and compliance requirements are maintained. - Ability to collaborate with software engineering, data analytics, security, and DevOps teams. - Ability to monitor and troubleshoot pipeline failures and data discrepancies. - Ability to participate in code reviews and continuously improve engineering practices. Attributes that will drive success: - Ability to work effectively in a collaborative, fast-paced environment. - Good written and verbal communication skills.