Data Engineer

Role & Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines using Snowflake and cloud technologies.
• Develop and optimize complex SQL queries for data transformation, reporting, and analytics.
• Build and maintain Snowflake data warehouse solutions, including data loading, transformation, and performance optimization.
• Implement data quality, validation, reconciliation, and error-handling processes.
• Work with Azure data services and cloud-based data pipelines.
• Develop data models using dimensional modeling and data warehousing concepts.
• Use dbt and/or Airflow for data transformation and pipeline orchestration.
• Monitor production data pipelines, troubleshoot issues, and perform root-cause analysis.
• Follow Git/version-control practices and participate in code reviews.
• Collaborate with architects, developers, QA teams, analysts, and business stakeholders.
• Prepare technical documentation and support Agile/Scrum development activities.

Preferred Candidate Profile

• 35 years of experience in Data Engineering, ETL/ELT, or Data Warehousing.
• Strong hands-on experience with Snowflake and Advanced SQL.
• Good programming experience in Python for data engineering/automation.
• Hands-on experience with Azure cloud data services.
• Strong understanding of ETL/ELT pipelines and Data Warehouse concepts.
• Experience with Data Modeling / Dimensional Modeling.
• Familiarity with dbt and/or Apache Airflow.
• Good understanding of Git/version control and software development practices.
• Experience with Azure Databricks, Spark/PySpark, ADF, Data Vault, or CI/CD will be an added advantage.
• Strong analytical, problem-solving, communication, and collaboration skills.
• Comfortable working independently in a production data engineering environment.