
Project Architect Jobot
- $120,000–$140,000 Per Year
| Location | Charlotte, NC |
Location: Charlotte, NC
Work Arrangement: Onsite
Job Type: Contract
Industry: Insurance
Experience: 12+ years
Rate: 55$/hr on C2C
We are seeking a highly experienced Senior Data Engineer / Data Architect with strong Databricks and Insurance domain experience to design, develop, and implement scalable enterprise data solutions.
The ideal candidate will have strong hands-on experience with Databricks, Apache Spark, Python, SQL, data engineering, cloud data platforms, data architecture, and insurance data. The candidate will work closely with business stakeholders, data architects, engineers, analysts, and technology teams to build modern data platforms and analytics solutions.
Design and develop scalable data architecture and data engineering solutions using Databricks.
Build and maintain robust ETL/ELT data pipelines using Databricks, Apache Spark, Python, and SQL.
Design data lakes, lakehouse architectures, data warehouses, and enterprise data platforms.
Develop high-performance batch and streaming data pipelines.
Implement data ingestion from multiple internal and external sources.
Develop data transformation, cleansing, validation, and integration processes.
Design scalable and reusable data models for analytics and reporting.
Work with Delta Lake, Delta Live Tables (DLT), Unity Catalog, and Databricks workflows where applicable.
Optimize Spark jobs, SQL queries, pipelines, and data-processing workloads.
Implement data quality, data governance, security, lineage, and access-control processes.
Collaborate with Data Scientists, BI teams, Business Analysts, Product Owners, and application teams.
Translate business requirements into technical data architecture and engineering solutions.
Participate in architecture reviews and establish data engineering best practices.
Troubleshoot production data issues and provide root-cause analysis.
Mentor junior and mid-level data engineers.
Support cloud migration and modernization initiatives.
Strong understanding of Property & Casualty (P&C), Life, Health, or other Insurance domain data is highly preferred.
Experience with insurance data such as:
Policy
Policyholder
Customer
Claims
Premium
Billing
Underwriting
Rating
Coverage
Loss
Agent / Broker
Payments
Risk
Product
Quote
Policy Administration
Experience integrating data from policy administration, claims, billing, underwriting, and other insurance applications is a strong plus.
Databricks
Apache Spark / PySpark
Python
SQL
Data Engineering
Data Architecture
ETL / ELT
Data Lake / Lakehouse
Delta Lake
Data Modeling
REST APIs / Data Integration
Git / CI/CD
Strong experience with at least one major cloud platform:
Microsoft Azure
AWS
Google Cloud Platform
Azure Databricks experience is highly preferred.
Experience with technologies such as:
Azure Data Factory
Azure Data Lake Storage
AWS S3
AWS Glue
Snowflake
Kafka
Airflow
is a plus.
Candidates should have experience with several of the following:
Databricks Workspace
Apache Spark
PySpark
Delta Lake
Delta Live Tables
Unity Catalog
Databricks Workflows
Databricks SQL
Cluster configuration and optimization
Performance tuning
Data governance
Data security
CI/CD for Databricks
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
8+ years of experience in Data Engineering, Data Architecture, or related roles.
Strong hands-on experience with Databricks and Spark.
Strong Python and SQL development experience.
Experience designing enterprise-scale data platforms.
Strong understanding of data modeling and data integration.
Experience working in Agile/Scrum environments.
Strong communication and stakeholder-management skills.
Insurance industry/domain experience is required or strongly preferred.
Databricks certification.
Cloud certification.
Experience with enterprise insurance platforms.
Experience with P&C insurance data.
Experience with data governance and master data management.
Experience with real-time/streaming data.
Experience with cloud migration and legacy modernization.
Experience leading data architecture initiatives.

