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.
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