Data Tech Lead with Java
Alpharetta GA (or) Berkley Hills NJ

1. Role Overview

Experienced 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.

Data Tech Lead with Java

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