Sr
Data Engineer Lead/ Architect with Azure Databricks and Unity Catalog (
candidate should be hands on)
Charlotte,
NC - 3 days office
Role Overview
We
are looking for an experienced Azure Databricks Engineer with strong expertise
in cloud-based data engineering, ETL development, and distributed data
processing. The ideal candidate should have solid hands-on experience with
PySpark, Delta Lake, Azure Data Factory, and building scalable data pipelines
on Azure.
The
engineer will work closely with business, Data Architects, and cross-functional
teams to design, develop, and optimize data pipelines for enterprise‑grade
analytics and reporting.
Key Responsibilities
- Data
Engineering & Pipeline Development
- Design,
develop, and optimize ETL/ELT pipelines using Azure Databricks (PySpark).
-
Build scalable data ingestion workflows from various structured and
unstructured sources.
-
Implement transformation logic, data cleansing, enrichment, and validation
frameworks.
-
Work with Delta Lake to build medallion architecture (Bronze/Silver/Gold
layers).
-
Develop reusable Databricks notebooks and jobs for production data workflows.
-
Azure Cloud & Integration
- Build
and orchestrate pipelines using Azure Data Factory (ADF).
-
Integrate Databricks with other Azure services—ADLS, Azure SQL, Event Hub, Key
Vault, Synapse.
-
Optimize compute environments (clusters, pools, autoscaling).
-
Implement DevOps processes using Git, CICD, Azure DevOps.
-
Performance, Quality & Governance
- Optimize
PySpark jobs for performance and cost efficiency.
-
Implement best practices for data governance, security, and access control.
-
Troubleshoot production issues and perform root-cause analysis.
-
Conduct code reviews ensuring coding standards and data quality.
-
Collaboration & Documentation
- Work
with Data Architects to define architecture and design patterns.
-
Prepare technical documents, solution diagrams, and runbooks.
-
Collaborate with business stakeholders to understand requirements and translate
them into technical solutions.
Mandatory Skills
- Azure
Databricks – notebooks, jobs, workflows, Delta Lake.
-
PySpark – dataframes, Spark SQL, optimization & debugging.
-
Azure Data Factory (ADF) – triggers, pipelines, integration runtime.
-
Data Lake Storage (ADLS Gen2) – folder structures, partitioning, security.
-
CI/CD – Git (branching strategies), Azure DevOps pipelines.
-
SQL – strong proficiency in writing optimized queries.
Good-to-Have Skills
- Azure
Synapse Analytics
-
Azure Event Hub / Kafka
-
Azure Functions
-
DataBricks REST APIs
-
Streaming pipelines (Structured Streaming)
-
Experience with data modelling
-
Knowledge of Lakehouse architecture
Behavioral & Soft Skills
- Strong
analytical and problem-solving skills.
-
Ability to work independently and in cross-functional teams.
-
Good communication skills for stakeholder interaction.
-
Comfortable working in Agile/Scrum models.
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06/22/26, 05:01:06 PM |
