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# Azure Senior Data Lead

- **Company:** HCL America Inc.
- **Location:** United States
- **Experience:** Expert
- **Salary:** $100,000 - $148,000
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Microsoft Azure, Big Data, Continuous Integration, Data Validation, Information Engineering, Data Governance, Extract Transform Load (ETL), Apache Hive, Python (Programming Language), Microsoft SQL Server, Oracle SQL Developer, Performance Tuning, Power BI, Azure Data Lake, SQL Databases, Data Streaming, Azure Service Bus, Cloud Platform System, Data Ingestion, Azure Data Factory, Apache Spark, Git, Microsoft Fabric, Data Lakes, Pyspark, Apache Kafka, Terraform, Data Pipelines, Databricks
- **Published:** November 13, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f7244fdec186df1a

## About the Role

* 9+ years of overall Data Engineering experience.
 * 4+years of hands-on Databricks/Spark experience preferred.
 * Experience delivering cloud-based data platforms on Microsoft Azure.

Must Have Skill

Azure Data Factory (ADF),Azure Databricks,MS SQL,Python,Oracle PL/SQL

## Description

We are looking for an experienced Databricks Data Engineer to design, develop, and maintain scalable data engineering solutions on the Azure cloud platform. The candidate should have strong hands-on experience with Azure Databricks, Apache Spark, PySpark, SQL, Delta Lake, and Azure Data Factory (ADF), with a solid understanding of modern data lakehouse architectures., * Design and develop scalable data pipelines using Azure Databricks, PySpark, Spark SQL, and Python.

 * Build and maintain ETL/ELT pipelines for batch and large-scale data processing.
 * Develop data ingestion and transformation workflows using Azure Data Factory (ADF).
 * Design and implement Delta Lake / Lakehouse solutions.
 * Work with Azure Data Lake Storage Gen2 (ADLS Gen2) for data ingestion, storage, and processing.
 * Develop optimized PySpark and SQL transformations for large datasets.
 * Implement Delta tables, schema management, data quality checks, and performance optimization.
 * Work with Databricks Workflows/Jobs for pipeline orchestration and scheduling.
 * Implement data governance and access controls using Unity Catalog.
 * Monitor pipelines, troubleshoot failures, and optimize Spark workloads.
 * Implement CI/CD processes using Azure DevOps and Git.
 * Collaborate with Data Architects, Data Analysts, BI teams, and business stakeholders.
 * Support downstream reporting and analytics solutions such as Power BI., Good to Have

 * Databricks SQL
 * Structured Streaming
 * Kafka or Event Hubs
 * Power BI
 * Terraform
 * CI/CD automation
 * Data modeling
 * Data quality frameworks
 * Microsoft Fabric exposure