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