Data Tech Lead with Java

CYNET SYSTEMS INC.

Raleigh, NC, United States

11 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Compensation

$126,880.0 - $137,280.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Java (Programming Language) Amazon Web Services Automation of Tests Microsoft Azure Cloud Database Extract Transform Load (ETL) Data Transformation Data Migration Electronic Data Interchange (EDI) Python (Programming Language) PostgreSQL NoSQL

+22 more

Performance Tuning Query Optimization Release Management Power BI Swagger SQL Databases Data Streaming Data Ingestion Cloud Monitoring Snowflake Grafana Data Lakes Pyspark Gitlab-ci Deployment Automation Cassandra Enterprise Integration Apache Kafka Restful APIs Stream Analytics Data Pipelines Databricks

Job 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.
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Requirements

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.