Data Engineer

Description

• Design, develop, and maintain Azure SQL databases, including schema design, stored procedures, indexing, and performance tuning.
  
• Build scalable data pipelines using Azure Data Factory, Azure Databricks, Azure Synapse, and related services.
  
Integrate data from diverse sources (APIs, on-prem databases, cloud systems) into Azure platforms.

Implement ETL/ELT processes and optimize workflow performance.

Work with structured and unstructured datasets to build reliable data models.

Collaborate with Data Analysts, BI Engineers, and Product teams to deliver high-quality data solutions.

Implement best practices for data quality, security, governance, and monitoring.

• Troubleshoot production issues, optimize query performance, and improve data reliability.

Key Responsibilities

• Strong expertise in Azure SQL, T-SQL, stored procedures, indexing, and query optimization.
  
Hands-on experience with Azure data services:
Azure Data Factory (ADF)

• Azure Synapse / Data Warehouse
  
  Azure Databricks / Spark (optional depending on role)
  
  Azure Blob Storage / Data Lake (ADLS)
  
Solid understanding of ETL/ELT concepts and data integration patterns.

• Experience with CI/CD, Git, and DevOps tools for data pipelines.
  
Familiarity with data modeling (Star/Snowflake), dimensional modeling, and warehouse architecture.

• Strong problem-solving, debugging, and performance tuning skills.

Skills, Knowledge & Expertise

• Experience with Python or PySpark for data engineering tasks.
  
Exposure to Power BI or data visualization tools.

Understanding of Azure security features (Key Vault, Managed Identity, RBAC).

Knowledge of Agile/Scrum methodologies.

Ability to work independently and in cross-functional teams.

• Detail-oriented with a focus on data accuracy and reliability.

About ParentPay Group