Job Description :

USEReady helps businesses to be self-reliant on data. Growing over 3000% since inception, USEReady achieved #113 rank in Inc 500 2015 and honoured top 100 companies in North America 2015 by Red Herring. USEReady is built on strong entrepreneurial spirit with unprecedented opportunities for career growth. At USEReady, we believe in achieving career growth while improving our individual competencies. If you desire to be part of a team that believes in mutual success and inspiration, you are welcome to apply.

USEReady helps enterprises apply AI and agentic intelligence to improve decisions, automate operations, and build smarter, more autonomous business systems.

For more than a decade, we have built the foundations that make this possible by.

Job Description :

We are looking for a Senior Azure Data Engineer with strong expertise in Databricks and Azure data services. The role involves designing, building, and optimizing scalable, secure, and high-performance data platforms, leveraging modern Lakehouse architecture and real-time data processing capabilities.

Key Skills :

- Strong hands-on experience with Databricks, including Notebooks (Python, SQL), SQL Editor, Unity Catalog, Delta Lake, Databricks Notification Alerts, Genie Spaces, and performance optimization.

- Expertise in Azure Data Factory (ADF) for ETL/ELT orchestration.

- Advanced Python, PySpark, and SQL skills with strong understanding of Spark performance tuning.

- Experience with Azure Data Lake Storage (ADLS Gen2), Azure Synapse Analytics, Azure SQL Database, and Azure Event Hub.

- Experience with real-time data ingestion using Structured Streaming, Kafka, Event Hubs, and Auto Loader.

- Hands-on experience with Spark Declarative Pipelines (SDP), Delta Live Tables (DLT), and Medallion Architecture.

- Strong understanding of data modeling, data warehousing, governance, lineage, and access control.

- Experience with GitHub, GitHub Actions, Azure DevOps, and CI/CD practices.

- Familiarity with Databricks Asset Bundles (DAB) and awareness of Lakeflow Connect for data ingestion.

Responsibilities :

- Design and develop scalable data pipelines using Databricks and ADF.

- Build and maintain Delta Lake tables and Lakehouse solutions for analytics and reporting.

- Implement governance and security using Unity Catalog.

- Optimize Databricks jobs, Spark workloads, and SQL queries for performance and cost efficiency.

- Develop and support real-time and batch data processing solutions.

- Configure Databricks Notification Alerts, SQL dashboards, and Genie Spaces to improve monitoring, self-service analytics, and business user adoption.

- Monitor, troubleshoot, and improve data pipeline reliability and quality.

- Collaborate with stakeholders to deliver business-focused data solutions.

- Mentor junior engineers and promote data engineering best practices.

Preferred Skills :

- 5+ years of Azure Data Engineering experience.

- Experience with large-scale distributed data processing systems.

- Databricks and/or Azure Data Engineering certifications preferred.

- Strong communication, collaboration, and problem-solving skills.