Description

You will design and implement hybrid data pipelines and automation frameworks across Azure and Snowflake ecosystems.

This role is on-site.

Responsibilities

• Build hybrid data pipelines using Azure Data Factory, Synapse, Databricks, Snowflake, and ADLS.
• Develop Python automation scripts for data quality validation, API orchestration, and custom ETL processes.
• Create enterprise Power BI semantic models, DAX measures, and paginated reports with Fabric integration and row-level security.
• Implement Power Automate flows for workflow automation across Service Bus, Teams, SharePoint, and vendor APIs.
• Deploy Python-based data quality frameworks and monitoring solutions integrated with Snowflake streams and Azure Purview.

Required Skills

• 5+ years of experience in data engineering.
• Strong proficiency in Python for ETL, automation, and Snowpark Python UDFs.
• Hands-on experience with Snowflake data modeling, including star schemas, materialized views, streams, and tasks.
• Expertise in Azure Data Factory, Synapse, and Databricks.
• Experience building Power BI semantic models and DAX measures.
• Familiarity with dbt for transformations and data quality validation.

Preferred Skills

• Snowflake certifications (SnowPro Core/Advanced) or Azure Data Engineer Associate (DP-203).
• Experience with Azure DevSecOps and Python ML libraries (scikit-learn).
• Bachelor's or Master's degree in Computer Science, Data Engineering, Statistics, or a related field.

Key Skills

Education

Bachelor's or Master's degrees