Databricks Developer / Data Architect

Job Description: Databricks Developer / Data Architect Position Title Databricks Developer / Data Architect Location Hybrid/ Remote Employment Type Full-Time / Contract Job Summary 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. Key Responsibilities Data Architecture & Modeling 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 ETL Development 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 Cloud & Platform Engineering 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 Required Skills & Qualifications 5+ years of experience in Data Engineering / Data Architecture Strong hands-on experience with Databricks platform Expertise in: - Python Apache Spark PySpark SQL Strong understanding of: - Lakehouse Architecture Medallion Architecture Data Modeling ETL/ELT Design Patterns Experience with cloud platforms: - Microsoft Azure AWS Experience integrating with: - PostgreSQL DynamoDB MongoDB Snowflake Cloudera Domino Server Knowledge of performance tuning and optimization in Spark/Databricks Experience with version control and DevOps practices Preferred Qualifications Databricks Certification(s) Experience with Delta Lake and Unity Catalog Familiarity with streaming frameworks and real-time data processing Knowledge of data governance and security best practices Experience in Agile/Scrum delivery models Technical Stack Databricks Python Spark / PySpark SQL Azure AWS Snowflake PostgreSQL MongoDB DynamoDB Cloudera Domino Server Soft Skills Strong analytical and problem-solving abilities Excellent communication and stakeholder management skills Ability to work independently and collaboratively in fast-paced environments Strong documentation and solution design capabilities Nice-to-Have Experience with Terraform or Infrastructure as Code Exposure to ML/data science platforms Experience with orchestration tools such as Airflow or Azure Data Factory