> Markdown version of [/jobs/ext/1956658-data-tech-lead-with-java](https://www.wearedevelopers.com/jobs/ext/1956658-data-tech-lead-with-java). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Tech Lead with Java - **Company:** CYNET SYSTEMS INC. - **Location:** Atlanta, GA, United States - **Experience:** Expert - **Salary:** $126,880.0 - $137,280.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Automation of Tests, Microsoft Azure, Cloud Database, Extract Transform Load (ETL), Data Transformation, Data Migration, Electronic Data Interchange (EDI), Python (Programming Language), PostgreSQL, NoSQL, Performance Tuning, Query Optimization, Release Management, Power BI, SQL Databases, Data Streaming, Data Ingestion, Cloud Monitoring, Snowflake, Grafana, Data Lakes, Pyspark, Gitlab-ci, Deployment Automation, Cassandra, Enterprise Integration, Apache Kafka, Stream Analytics, Data Pipelines, Databricks - **Published:** August 6, 2026 - **Apply:** https://www.careerjet.com/jobad/usc305578c51a3901b84ffe634492341b1 ## About the Role * 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. ## Description * 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., We are seeking a Technical Lead with over 10 years of relevant experience in modern technologies to provide architectural direction, technical guidance, and delivery oversight acro… ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [5 steps for running a Kubernetes environment at scale](https://www.wearedevelopers.com/videos/88-5-steps-for-running-a-kubernetes-environment-at-scale) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)