Senior Cloud Data Engineer

SUMMARY:
Are you an experienced Data Engineer looking to take your career to the next level? Join my client, where you'll play a crucial role in designing, building, and supporting modern data engineering solutions within the Azure data platform.

POSITION INFO:
Key Focus Areas: Reporting to the Data Engineer Practice Manager, your responsibilities will include:

• Designing, building, and supporting modern data engineering solutions in the Azure data platform.
• Collaborating closely with cross-functional teams within, including Infrastructure DevOps, solution architects, subject matter experts, and data modelers.
• Working collaboratively with vendors to ensure data engineering practices meet the company's standards.
• Maintaining, supporting, and monitoring existing production Azure Synapse data engineering pipelines, PySpark notebooks, data platform lake house architecture, and Azure SQL ODS storage.
• Participating in Azure data platform architecture design, data modeling, and analysis of data requirements.
• Promoting data engineering best practices with CICD YAML pipelines and automation.
• Coaching and mentoring junior data engineers on Azure technologies.
• Contributing significantly to building a high-performing, collaborative, and result-driven data engineering team.
• Supporting the Data Engineering Practice Team Manager with best-fit data engineering solutions and high-standard documentation.
• Following data ethics standards to protect personal information and meet stakeholders' expectations.

• 10+ years of demonstrable experience in designing, building, and supporting data engineering pipelines in data warehousing, BI analytics, and/or ML space, including 5+ years of experience using Azure data analytics tools.
• Microsoft Azure Data Engineering Associate (DP-203) certification.
• Bachelor's or master's degree in computer/data science or related field.
• Strong knowledge and extensive experience in implementing modern lake house architecture on Azure Data Lake Gen2 and Apache Spark using PySpark.
• Extensive experience in metadata-driven data engineering pipeline design and development.
• Strong data modeling knowledge and experience with Dimensional and/or Data Vault methodologies.
• Experience working in an Agile framework with CI/CD using modern DevOps/DataOps processes.
• Desirable knowledge of machine learning, MLOps, AI, and IaC such as BICEP and/or Terraform.
• Experience manipulating semi-structured data (XML, JSON).

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