Data Engineer

About the Role We are looking for a Senior Data Engineer with strong experience in modern data platforms and cloud-based architectures. The ideal candidate has deep hands-on experience with Snowflake or Databricks, has built scalable data pipelines, and is proficient in Azure cloud services. Key Responsibilities - Design, build, and maintain scalable data pipelines and ETL/ELT workflows. - Develop and optimize data lake and data warehouse solutions using Snowflake and/or Databricks. - Implement data ingestion, transformation, and processing frameworks for structured and unstructured datasets. - Work closely with cross-functional teams (Data Analytics, Data Science, Product, Engineering) to support data consumption needs. - Build reusable and modular data pipeline components aligned with best practices. - Implement data quality validation, reconciliation, and monitoring controls. - Optimize performance for data storage, compute, and query execution. - Ensure adherence to data governance, security standards, and compliance requirements. - Participate in solution architecture discussions and contribute to technical design decisions. Required Skills & Experience - 7–8+ years of hands-on experience as a Data Engineer. - Strong experience in Snowflake and/or Databricks (any one is fine, both preferred). - Hands-on experience on Azure Cloud (e.g., Azure Data Factory, ADLS, Azure Synapse, Azure Key Vault, Azure Functions, Azure DevOps). - Expertise in SQL and performance tuning for large datasets. - Experience developing ETL/ELT pipelines using modern data frameworks. - Proficiency with scripting languages such as Python or Scala. - Experience with data modeling techniques (star schema, normalized models, dimensional modeling). - Experience with CI/CD for data pipelines and version control (Git). - Exposure to data governance, metadata management, and data quality frameworks.