Full-Time Engineering Lead Analyst

Lead Data Engineer: Spearhead data engineering teams, driving them to the next level.

Role Responsibilities:

• Infrastructure Migration: Migrate legacy data infrastructure ensuring performance, security, and scalability.
• Data System Development: Build and optimize data systems, pipelines, and analytical tools using a bronze-silver-gold architecture.
• Databricks Implementation: Develop and configure Databricks notebooks and pipelines for data ingestion from on-premise and cloud environments, following Databricks standards.
• Stakeholder Collaboration: Translate business needs into robust data solutions and communicate technical progress, risks, and recommendations to stakeholders.
• Data Governance: Implement strong data governance and access control mechanisms for data quality, security, and compliance.
• Data Analysis: Conduct advanced data analysis to support decision-making and reporting.
• QA Testing: Apply QA testing practices within data workflows, especially in healthcare environments.
• Data Initiatives: Drive data discovery, lineage, and quality initiatives across the organization.

Skills & Experience:

• Background: Bachelor's degree in Computer Science, Engineering, or a related field.
• Experience: 5+ years of hands-on data engineering experience, with at least 2 years in Azure or Databricks.
• Cloud Experience: Expertise in Azure Cloud, CI/CD pipelines, and Agile methodologies.
• Databricks Proficiency: Proficiency in Databricks notebooks, data engineering frameworks, and Pyspark (preferred).
• Programming: Strong Python programming skills for data processing and automation.
• SQL Proficiency: Advanced SQL skills for querying and transforming large datasets.
• Data Modeling: Solid understanding of data modeling, warehousing, and performance optimization.
• Data Cataloguing: Proven experience in data cataloging and inventorying large-scale datasets.
• Leadership: Strong ability to work independently, lead, and mentor junior data engineers.

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