Senior Data Engineer

Overview:

• This role will focus on building and optimizing modern ETL/ELT pipelines, improving data usability, and supporting cloud-based data modernization initiatives across Azure environments. The ideal candidate has strong hands-on experience with SQL, Python, cloud data engineering, and enterprise-scale data pipelines, along with a passion for making complex data accessible, governed, and actionable.
• This is a highly collaborative role working closely with data architects, analysts, product teams, and business stakeholders to build reliable, high-performing data solutions.

Responsibilities:

• Design, develop, and optimize scalable ETL/ELT pipelines supporting enterprise data products
• Build and maintain cloud-native data workflows across Azure-based platforms and modern data ecosystems
• Transform raw enterprise data into curated, business-ready datasets for external users and downstream applications
• Develop and maintain data models, ingestion pipelines, and transformation frameworks
• Write and optimize complex SQL and Python-based data processing workflows
• Improve data quality, governance, lineage, and reliability across the data platform
• Support modernization initiatives involving cloud data warehouses, lakehouse platforms, and enterprise reporting systems
• Implement CI/CD and DevOps best practices for data engineering workflows and deployments
• Collaborate with cross-functional teams to gather requirements and deliver scalable data solutions
• Troubleshoot and optimize pipeline performance, scalability, and operational reliability

Required:

• 8+ years of experience in data engineering, ETL development, or data warehousing
• Strong proficiency with SQL and Python
• Experience building and maintaining ETL/ELT pipelines in enterprise environments
• Hands-on experience with Azure cloud services such as ADF, Synapse, ADLS, or related technologies
• Experience with data modeling, transformation, and large-scale data processing
• Experience implementing CI/CD automation and DevOps workflows for data engineering
• Strong understanding of data governance, lineage, and secure data practices
• Excellent problem-solving, communication, and collaboration skills

Preferred:

• Experience with Databricks, Spark, PySpark, Snowflake, or Lakehouse architectures
• Exposure to Delta Lake, Unity Catalog, or modern governance tooling
• Experience working within regulated enterprise environments such as financial services or healthcare
• Experience supporting data products, analytics platforms, or external-facing data solutions