ETL Data Engineer

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.