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Mid-level data engineer title, metro location, and known IT brand create high applicant competition.
Data engineering skills are transferable, but Azure/Snowflake specialization moderately limits cross-industry fit.
Explicit 4-7 years, mandatory Azure/Snowflake/Databricks skills and certifications increase shortlisting strictness.
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Develop and maintain scalable data pipelines using Snowflake, Azure Data Factory (ADF), and Databricks to meet business requirements.
Collaborate with stakeholders to gather requirements and translate them into technical specifications for data models, flows, and ETL processes.
Optimize, troubleshoot, and implement data security measures ensuring high performance and reliability of data solutions.
4 to 7 years of experience in data engineering with hands-on skills in ADF, Azure Databricks, Spark, and Synapse.
Experience developing SQL queries, Spark programming, and building data ingestion pipelines including reading data from APIs.
Certifications required: Snowflake SnowPro Core and Microsoft Certified: Azure Data Engineer Associate.
Work Experience Required: 4 to 7 years. Notice period: Not explicitly mentioned.
Experienced in designing and optimizing large-scale data pipelines using Azure and Snowflake technologies.
Able to translate business requirements into technical deliverables including data mapping and ETL processes.
Familiar with handling data ingestion from APIs and integrating with systems like Braze via data lakes and pipelines.