ETL Data Engineer Python Snowflake

Position Overview

We are seeking a hands-on Data Engineer to join a growing organization focused on building and optimizing scalable, cloud-native data pipelines. This role is centered on designing and delivering robust ETL solutions using Python, PySpark, and Microsoft Azure data services, with a strong emphasis on modern data warehouse architecture and high-performance data processing.

The environment is evolving toward a Snowflake-based architecture in the next 6 months, so experience with or exposure to cloud data platform migrations is a strong plus.

• Design, build, and maintain scalable ETL data pipelines using Python and Py Spark
• Develop and optimize ETL workflows within Microsoft Azure ecosystem
• Leverage Azure Synapse Analytics for pipelines, notebooks, and distributed data processing
• Build and manage data workflows using Azure Data Factory, including linked services, triggers, and monitoring
• Develop secure and efficient data solutions leveraging Azure Key Vault
• Integrate data from multiple sources including REST APIs, relational databases, flat files (CSV), and external systems
• Design and implement scalable data warehouse models using star schema and dimensional modeling best practices
• Ensure data quality, governance, lineage, security, and performance tuning across pipelines
• Collaborate closely with data architects, analysts, and business stakeholders to translate requirements into scalable data solutions
• Support reporting and analytics use cases across tools such as Power BI and Tableau
• Participate in modernization efforts including lakehouse architectures, Git-based development, and Azure Dev Ops CI/CD workflows
• Explore and apply hands-on AI/ML techniques for data enrichment and automation where applicable

• Strong hands-on experience with Python and Py Spark
• Deep expertise in ETL pipeline development and optimization
• Strong SQL skills with experience in complex query development and tuning
• Solid understanding of data warehousing concepts, including dimensional modeling and star schema design
• Experience working in Microsoft Azure data ecosystem, including Synapse and related services
• Familiarity with data lake / lakehouse architectures
• Strong understanding of data quality, governance, and performance optimization principles
• Excellent communication skills with ability to work directly with technical and non-technical stakeholders
• Strong interpersonal skills and ability to thrive in a collaborative, fast-paced environment

• Exposure to Snowflake or cloud data warehouse migrations (expected platform transition within ~6 months)
• Experience with Git, Azure Dev Ops, or CI/CD pipelines
• Familiarity with Power BI or Tableau
• Experience applying AI/ML techniques in data engineering workflows

This is a high-impact engineering role in a modern data environment where you will help shape the evolution of enterprise data architecture—from Azure Synapse-based systems toward a next-generation Snowflake-centric platform. You will work across engineering, analytics, and business teams in a highly collaborative and technically forward-thinking organization.