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.
