What are the responsibilities and job description for the Sr. Azure Data Engineer position at O2 Technologies,Inc?
About The Role
Job Number 1
Sr Data Engineer Lead/ Architect with Azure Databricks and Unity Catalog ( candidate should be hands on)
Banking client
Charlotte NC-3 days office
Visa – any
10 months
Rate - $80-90/hr depending on experience – flexible for super strong resource
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.
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.
Azure Event Hub / Kafka
Azure Functions
DataBricks REST APIs
Streaming pipelines (Structured Streaming)
Experience with data modelling
Knowledge of Lakehouse architecture
Ability to work independently and in cross-functional teams.
Good communication skills for stakeholder interaction.
Comfortable working in Agile/Scrum models.
Key Responsibilities & Skills
Bachelor's Degree in Computer Science, Software Engineering, Information Systems, Data Science, Electrical Engineering, Computer Engineering. Preferred: Master's in Data Science, Master's in Computer Science, Master's in Information Systems, MBA (Technology Management).
Industry Experience
Job Number 1
Sr Data Engineer Lead/ Architect with Azure Databricks and Unity Catalog ( candidate should be hands on)
Banking client
Charlotte NC-3 days office
Visa – any
10 months
Rate - $80-90/hr depending on experience – flexible for super strong resource
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
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 Event Hub / Kafka
Azure Functions
DataBricks REST APIs
Streaming pipelines (Structured Streaming)
Experience with data modelling
Knowledge of Lakehouse architecture
- Behavioral & Soft Skills
Ability to work independently and in cross-functional teams.
Good communication skills for stakeholder interaction.
Comfortable working in Agile/Scrum models.
Key Responsibilities & Skills
- Azure Databricks (Notebooks, Jobs, Workflows, Delta Lake)
- PySpark (DataFrames, Spark SQL, Optimization & Debugging)
- Azure Data Factory (Triggers, Pipelines, Integration Runtime)
- Data Lake Storage (ADLS Gen2) – Folder Structures, Partitioning, Security
- CI/CD – Git (Branching Strategies), Azure DevOps Pipelines
- SQL – Optimized Query Development
- ETL/ELT Pipeline Development
- Medallion Architecture (Bronze/Silver/Gold)
- Data Governance & Security
- Performance Optimization & Cost Efficiency
- Cross-Functional Collaboration
- Technical Documentation & Runbooks
- Agile/Scrum Delivery
- Azure Databricks / Delta Lake / PySpark
- Azure Data Factory / Azure Synapse Analytics
- ADLS Gen2 / Azure Blob Storage
- Azure DevOps / Git
- SQL / Azure SQL Database
- Event Hub / Kafka
- Azure Functions
- Structured Streaming
- Lakehouse Architecture
Bachelor's Degree in Computer Science, Software Engineering, Information Systems, Data Science, Electrical Engineering, Computer Engineering. Preferred: Master's in Data Science, Master's in Computer Science, Master's in Information Systems, MBA (Technology Management).
Industry Experience
- Banking / Financial Services
- Cloud Data Engineering
- Enterprise Analytics
- Azure Cloud Platform
- Data Warehouse & Lakehouse Solutions
Salary : $80 - $90