Senior Data Engineer - Databricks / Azure Lakehouse POST NUMBER: 467024
Our client is a technology-forward financial services organization operating in a highly regulated environment where data quality, governance, and reliability are non-negotiable. This team is responsible for building and modernizing a cloud-native data platform that supports analytics, reporting, and downstream application use across the business.
This is a hands-on Databricks-focused data engineering role centered on building production-grade pipelines and governed data models. The work here directly supports decision-making, compliance, and operational visibility across the enterprise.
What You’ll Do
Design, build, and optimize large-scale data pipelines using the Databricks Lakehouse platform
Develop ETL and ELT workflows using Python, PySpark, and Spark SQL
Implement and manage Delta Lake data models for performance, reliability, and scalability
Apply strong governance practices using Unity Catalog, including RBAC, lineage, and secure data sharing
Modernize and extend an Azure-based data ecosystem supporting enterprise analytics
Build reusable frameworks and workflows using Databricks Workflows, Repos, and Delta Live Tables
Enable downstream consumption for BI, analytics, and data science use cases
Collaborate with stakeholders across engineering, analytics, and the business
Support CI/CD pipelines, testing, and production deployments
Required Skills & Experience
5 plus years of professional data engineering experience in production environments
Strong expertise in Databricks and Lakehouse architectures
Advanced proficiency with Python, PySpark, and Spark SQL
Experience designing and optimizing Delta Lake data models
Hands-on experience with Azure cloud services supporting data platforms
Familiarity with Unity Catalog for governance, security, and metadata management
Experience building end-to-end data pipelines with ownership from ingestion through consumption
Strong understanding of data quality, compliance, and enterprise data standards
Preferred / Nice-to-Have
Experience working with financial, healthcare, or other regulated datasets
Familiarity with Azure Data Factory, Data Lake, Key Vault, and related services
Experience with orchestration tools such as Apache Airflow
Exposure to CI/CD using Azure DevOps or similar tooling
Experience supporting BI, analytics, or reporting teams
Background working in matrixed or cross-functional enterprise environments
A Special Note to Applicants
- The current volume of automated and AI-generated applications is on the rise. If you have read this posting in full and believe this role genuinely aligns with your experience, we encourage you to apply thoughtfully.
- Applicants who include the word “Blue Steel”somewhere in their resume or cover note, or who reach out directly via LinkedIn to the recruiter who appreciates a good Zoolander reference, will help us route submissions more effectively
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