Senior Data Engineer

• Develop Data Pipelines: Create and maintain ETL pipelines to move data into centralized storage, ensuring data quality and integrity.
• Integrate Data: Combine data from various sources, including databases, APIs, and external providers, to build a unified data foundation.
• Data Transformation: Clean, normalize, and aggregate data for analysis, reporting, or machine learning.
• Best Practices & Frameworks: Develop and implement frameworks for data pipeline development, deployment, and automation.
• Data Governance: Enforce data governance standards.
• Collaborate with Teams: Work with analytics, product, and infrastructure teams to advance data and analytics platforms.
• Monitor Systems: Ensure the reliability of data systems through monitoring, issue detection, and automated error handling.

• Experience in designing data solutions and data modeling.
• Strong skills in developing data processing jobs using PySpark or SQL.
• Proficiency in data pipeline orchestration tools like ADF or Airflow.
• Experience with real-time and batch data processing.
• Familiarity with building data pipelines on Azure.
• Proficient in SQL and experienced with advanced features like Window functions.
• Understanding of DevOps, CI/CD pipelines, and Git workflows.
• Capable of working with both business and technical stakeholders.

• Bachelor’s degree in a relevant field.
• 3-5 years of data engineering experience.
• Experience with agile/scrum methodologies.
• Knowledge of Azure Data Factory, Databricks, Snowflake, and shell scripting.
• Proficiency in Python, especially for data-related tasks.
• Familiarity with Apache Spark, Kafka, Kubernetes, Docker, and cloud infrastructure management (e.g., Terraform).
• Experience in ML/AI model development and deployment is a plus.

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Mason Alexander