Revalsys Technologies - Data Engineer - Azure Databricks/PySpark

We are a team of data scientists, data engineers and business analysts who work with 1M+ data points every day.

Our combined experience in the industry is over 40 years.

Our market opportunity is massive, spanning billions of dollars globally.

We have a strong product-market fit with customers like big retail brands in GCC regions such as Lulu and GMG.

What sets us apart is our unique approach to data engineering.

As a bootstrapped company with over 100 people, we still prioritize innovation and hiring talented individuals like you.

Key Responsibilities :

- Design, develop, and optimize big data pipelines using Azure Databricks, PySpark, and Delta Lake.

- Work with Azure Data Lake, Azure Synapse, Azure SQL Database, and Azure Data Factory to implement robust data solutions.

- Develop and maintain ETL/ELT workflows for efficient data ingestion, transformation, and processing.

- Implement data governance, security, and compliance best practices in Azure environments.

- Optimize Databricks clusters, workflows, and cost efficiency in cloud environments.

- Collaborate with data scientists, analysts, and business stakeholders to ensure high-quality data solutions.

- Implement CI/CD pipelines for data engineering workflows using Azure DevOps.

- Ensure data quality, lineage, and observability using tools like Great Expectations, Unity Catalog, and Databricks SQL.

Certifications Required Qualifications & Skills :

- Databricks Certified Data Engineer Associate (Preferred)

- Databricks Certified Data Engineer Professional (Preferred)

Technical Skills :

- Azure Cloud Services : Azure Databricks, Azure Data Factory, Azure Data Lake, Azure Synapse, Azure Functions

- Big Data & ETL : PySpark, SQL, Delta Lake, Kafka (Preferred)

- Programming : Python, SQL, Scala (Optional)

- Orchestration & Automation : Airflow, Azure DevOps, GitHub Actions

- Data Governance & Security : Unity Catalog, RBAC, PII masking

- Performance Optimization : Spark tuning, Databricks cluster configuration, z-ordering

Preferred Experience :

- 2-4 years of experience in data engineering with a focus on Azure and Databricks.

- Experience working in high-volume, real-time streaming environments.

- Strong understanding of data modeling, warehousing, and governance best practices