Role Summary:
Lead the design development and optimization of enterprise scale data platforms and analytics solutions using Azure Databricks Drive data engineering best practices mentor team members and collaborate with business stakeholders to deliver scalable secure and high performance data solutions This aligns with Chevrons Azure based Data Analytics ecosystem.
Key Responsibilities
Lead the development of scalable data pipelines and ETLELT frameworks using Azure Databricks and PySpark
Architect and optimize data ingestion transformation and consumption layers
Design data models data dictionaries and reusable data products
Implement data governance quality security and compliance standards
Optimize Spark workloads Databricks jobs and overall platform performance
Collaborate with business users data scientists and cross-functional teams to translate requirements into technical solutions
Mentor and guide data engineers and junior team members
Drive CICD automation and DevOps best practices for data platforms
Support Data Lakehouse architecture and enterprise analytics initiatives
Required skills
Required Skills:
Azure Databricks
PySpark Apache Spark
Python
SQL TSQL
Azure Data Factory ADF
Azure Data Lake Storage ADLS
Azure Synapse Analytics
Delta Lake
Databricks Workflows
Data Modeling Data Warehousing
Azure DevOps
Data Governance Security
Performance Tuning and Optimization
CICD and Automation Frameworks
Experience
10 years in Data Engineering Data Platform delivery
Strong experience leading Azurebased cloud data transformation programs
Proven expertise in enterprisescale Databricks implementations
Experience mentoring teams and driving technical governance
Preferred Skills
Unity Catalog
Airflow
Power BI
Lakehouse Architecture
Data-Ops, ML-Ops exposure
Stakeholder management and client facing communication
