Data Tech Lead with Java

Data Tech Lead with JavaAlpharetta GA (or) Berkley Hills NJ1. Role OverviewExperienced Data Technical Lead to design, develop, and support scalable cloud-based data platforms and streaming data pipelines.The ideal candidate should possess strong expertise in Databricks, PySpark, Python, Java-based streaming technologies, GitLab CI/CD pipelines, and cloud migration initiatives.2. Key Responsibilities- Design and develop scalable Databricks ETL/ELT pipelines (Lakeflow & LakeBase) using Azure Databricks, PySpark, and Python.- Implement real-time and batch data ingestion frameworks using Kafka and Java-based streaming solutions.- Develop and optimize data processing workflows in Azure Databricks.- Integrate and manage data movement between PostgreSQL, YugabyteDB (Cassandra-based NoSQL), and cloud platforms.- Build reusable frameworks for data ingestion, transformation, validation, and orchestration.- Develop SQL-based data transformations, reporting datasets, and performance optimization solutions.- Design and implement GitLab CI/CD pipelines for automated deployment, testing, and release management of Databricks notebooks, jobs, and data pipelines.- Support Snowflake on-premises to Azure cloud migration initiatives.- Ensure coding standards, performance tuning, monitoring, and operational stability of data pipelines.- Develop Power BI dashboards and reports for business intelligence and analytics reporting.- Develop API automation and integration solutions for data exchange between enterprise systems.3. Required Skills.- Strong experience in Python and PySpark development.- Hands-on experience with Azure Databricks and databricks SQL.- Experience in Java-based streaming and ingestion frameworks.- Strong knowledge of Apache Kafka streaming concepts.- Experience working with PostgreSQL databases.- Experience with YugabyteDB or Cassandra-based NoSQL databases.- Strong SQL development and query optimization skills.- Hands-on experience with GitLab CI/CD pipeline development and deployment automation.- Understanding cloud-based data engineering and distributed processing concepts.- Experience in data migration projects, especially Snowflake on-prem to Azure cloud migration.- Experience designing enterprise-scale data lake or lakehouse architectures.- Knowledge of streaming architectures and real-time analytics.- Familiarity with cloud monitoring and observability tools