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Key skills for this role
We are seeking an experienced Databricks Developer / Data Architect to design, implement, and optimize modern data platforms and ETL pipelines using Databricks and cloud-native technologies. The ideal candidate will have strong expertise in data architecture, Lakehouse implementation, Medallion Architecture, and scalable ETL development across Azure and AWS environments.
The role involves setting up Databricks workspaces, configuring data integrations and Lakehouse Federation, building enterprise-grade ETL workflows, and enabling high-performance analytics solutions.
Databricks Developer / Data Architect
Full-Time / Contract
We are seeking an experienced Databricks Developer / Data Architect to design, implement, and optimize modern data platforms and ETL pipelines using Databricks and cloud-native technologies. The ideal candidate will have strong expertise in data architecture, Lakehouse implementation, Medallion Architecture, and scalable ETL development across Azure and AWS environments.
The role involves setting up Databricks workspaces, configuring data integrations and Lakehouse Federation, building enterprise-grade ETL workflows, and enabling high-performance analytics solutions.
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Design and implement scalable enterprise data architectures using Databricks Lakehouse platform
Configure and manage Databricks workspaces, clusters, access controls, and governance
Implement Medallion Architecture (Bronze, Silver, Gold layers) for data processing and analytics
Set up and manage Lakehouse Federation and data connectors for multi-source integration
Develop logical and physical data models for structured and semi-structured datasets
Ensure data quality, security, scalability, and performance optimization
Develop and maintain scalable ETL/ELT pipelines using PySpark, Spark SQL, and Databricks workflows
Build reusable data ingestion frameworks for batch and streaming workloads
Optimize Spark jobs for performance, cost efficiency, and reliability
Integrate data from relational and NoSQL databases, cloud platforms, and external systems
Automate deployment and monitoring of ETL workflows
Work with Azure and AWS cloud services to deploy and manage data solutions
Configure integrations with Snowflake, Postgres, MongoDB, DynamoDB, Cloudera, and Domino Server
Support CI/CD, infrastructure automation, and environment management
Collaborate with cross-functional teams including Data Scientists, Analysts, and Business stakeholders
Databricks
Python
Spark / PySpark
SQL
Azure
AWS
Snowflake
PostgreSQL
MongoDB
DynamoDB
Cloudera
Domino Server
Experience with Terraform or Infrastructure as Code
Exposure to ML/data science platforms
Experience with orchestration tools such as Airflow or Azure Data Factory
Verified company details for this employer are not available yet.
Full Time, Contract
Senior · 5+ years experience
Hybrid
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