About the Opportunity :

We are looking for a skilled Azure Data Engineer / Data Engineer with hands-on experience in Azure Data Factory, Snowflake, Databricks, and DBT to architect and implement large-scale data integration and transformation pipelines.

The ideal candidate will bring deep technical expertise in ETL/ELT design, data modeling, and big data processing, along with proficiency in Python and SQL for automating and optimizing complex data workflows.

Youll work in a high-impact role building and maintaining cloud-native data solutions that enable analytics, AI, and business intelligence initiatives across the organization.

This position is ideal for professionals passionate about designing high-performance, scalable, and secure data systems that serve as the backbone for enterprise decision-making.

What Youll Do :

- Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory and Databricks for data ingestion, transformation, and orchestration.

- Implement data integration and transformation frameworks in Snowflake, ensuring high performance and scalability.

- Develop modular and reusable data pipelines with DBT for data transformation, lineage tracking, and testing.

- Build and manage data lakes and data warehouse solutions leveraging Azure Data Lake Storage (ADLS) and Snowflake.

- Write optimized SQL and Python scripts for data processing, validation, and automation.

- Collaborate with data scientists, BI developers, and product teams to ensure data availability, quality, and reliability.

- Design and implement data models (star/snowflake schemas) for analytics and reporting workloads.

- Optimize Spark and Databricks jobs for cost, performance, and scalability.

- Establish data quality validation, error handling, and automated monitoring frameworks.

- Integrate CI/CD pipelines for data workflows, ensuring repeatable, version-controlled deployments.

- Ensure compliance with data governance, security policies, and industry regulations.

What You Bring :

- 6 to 10 years of professional experience in data engineering or ETL development, with a focus on cloud data platforms.

- Hands-on experience with Azure Data Factory, Azure Databricks, and Snowflake.

- Proficiency in SQL and Python for developing transformation logic, validation, and automation scripts.

- Expertise in data warehousing concepts, data lake architectures, and big data processing.

- Experience with DBT (Data Build Tool) for transformation management, modular pipelines, and testing.

- Strong understanding of Spark, Delta Lake, and Parquet for distributed data processing.

- Working knowledge of ETL/ELT pipeline orchestration, metadata management, and data lineage tracking.

- Experience implementing CI/CD pipelines and DevOps for data workflows.

- Familiarity with Azure cloud services, including ADLS, Synapse, and Key Vault.

- Strong analytical, troubleshooting, and performance optimization skills.

- Bachelors or Masters degree in Computer Science, Data Engineering, or related field.

Preferred Skills :

- Experience with data governance frameworks, role-based security, and compliance standards.

- Familiarity with AWS Redshift or GCP BigQuery for multi-cloud data integration.

- Exposure to Airflow, Prefect, or other workflow orchestration tools.

- Understanding of ML pipelines and feature store management within data ecosystems.

- Certifications in Azure Data Engineer, Snowflake, or Databricks are a plus