Role OverviewThis role requires a Senior Data Engineer with 11+ years of experience designing, building, and optimizing enterprise-scale data platforms, Lakehouse architecture, and analytics solutions in Azure cloud ecosystems. The ideal candidate will have proven expertise in developing scalable data pipelines, ETL/ELT frameworks, and cloud-native data solutions using Python, Spark, Azure Databricks, Azure Data Factory, Iceberg, Redshift, Synapse, S3, and ADLS Gen2 to support high-volume data processing, advanced analytics, and business intelligence.
What You Will Do
The responsibilities of this role include designing and implementing scalable Lakehouse and data platform architectures, developing and maintaining high-performance ETL/ELT pipelines, designing and optimizing data models, data warehouses, and semantic layers, and building cloud-native solutions using Azure technologies.
Why It Might Be a Fit
The ideal candidate will have experience with Power BI or other data visualization tools, exposure to cloud certifications, knowledge of REST APIs and web frameworks, and experience with stakeholder engagement and requirements gathering.
Requirements
- 11+ years of experience designing, building, and optimizing enterprise-scale data platforms, Lakehouse architecture, and analytics solutions in Azure cloud ecosystems
- Proven expertise in developing scalable data pipelines, ETL/ELT frameworks, and cloud-native data solutions using Python, Spark, Azure Databricks, Azure Data Factory, Iceberg, Redshift, Synapse, S3, and ADLS Gen2
- Experience with Power BI or other data visualization tools
- Exposure to cloud certifications (e.g., Azure Cloud Practitioner)
- Knowledge of REST APIs and web frameworks (e.g., Flask)
- Experience with stakeholder engagement and requirements gathering
Benefits
- medical, dental, vision, pharmacy, life, accidental death & dismemberment, and disability insurance
- employee assistance program
- 401(k) retirement plan
- 10 days of paid time off per year
- 10 paid holidays per year
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