Role Overview :

We are looking for an experienced Data Engineer with strong hands-on expertise in Azure data services and Databricks to design, build, and optimize scalable data pipelines and modern data platforms. The role will work closely with analytics, BI, business, and engineering teams to deliver reliable and high-performance data solutions.

Key Responsibilities :

- Design, develop, and maintain scalable data pipelines using Azure Databricks.

- Build and optimize ETL/ELT workflows using PySpark, Python, and SQL.

- Develop data ingestion and transformation pipelines using Azure Data Factory.

- Work with Azure Data Lake Storage (ADLS) and Azure Synapse Analytics for enterprise data processing and warehousing.

- Design and implement data models, curated datasets, and data layers to support analytics and BI reporting.

- Support Power BI and/or Tableau reporting environments by providing reliable, optimized, and well-structured datasets.

- Implement data validation, quality checks, monitoring, and error-handling mechanisms across pipelines.

- Optimize Databricks jobs, Spark workloads, SQL queries, and data pipelines for performance and scalability.

- Implement data engineering solutions aligned with security, governance, and data management standards.

- Work with Delta Lake and Lakehouse architecture to build modern data platforms.

- Collaborate with Data Scientists, BI Developers, Analysts, Business Teams, and Engineering teams to understand requirements and deliver data solutions.

- Troubleshoot production data issues and perform root-cause analysis.

- Contribute to automation, documentation, coding standards, and continuous improvement of data engineering processes.

Required Candidate Profile :

- 5 - 10 years of experience in Data Engineering, with strong hands-on experience in Azure data platforms.

- Strong expertise in Azure Databricks, PySpark, and SQL.

- Hands-on experience with Azure Data Factory, ADLS, and Azure Synapse Analytics.

- Strong understanding of ETL/ELT development and data pipeline architecture.

- Experience with data warehousing concepts and dimensional data modelling.

- Experience developing curated datasets and data models for BI and analytics.

- Exposure to Power BI and/or Tableau reporting environments.

- Strong experience in performance tuning and optimization of Spark jobs, SQL queries, and data pipelines.

- Good understanding of data quality, governance, security, and access controls.

- Strong problem-solving and stakeholder communication skills.

Preferred Skills :

- Experience with Delta Lake and Lakehouse architecture.

- Strong Python programming and workflow orchestration experience.

- Experience with Databricks Workflows and job scheduling.

- Exposure to cloud security and enterprise data governance.

- Experience working on large-scale enterprise analytics or data platforms.