Data Engineer Azure Retail Lead

il y a 1 semaine

Paris, Île-de-France LINCOLN Temps plein

Job Summary

The Tech Lead / Senior Data Engineer will lead and contribute to the design, development, maintenance, and evolution of AI and Data Products. This highly technical role aligns with delivering business value as you will be working within an AI and Data Product team.

Key Responsibilities

  • Lead Design and Development
    • Spearhead the design, implementation, and optimization of batch and real-time data ingestion pipelines using tools like Databricks (with PySpark) and DBT.
    • Ensure that raw data is cleansed, transformed, and enriched to be analytics-ready while optimizing data processing for speed and cost-efficiency.
  • Architect & Manage Data Systems
    • Design and implement robust database schemas, tables, and views.
    • Optimize storage formats such as Parquet or Delta Lake, enforce data quality checks, and document data lineage.
    • Implement partitioning, bucketing, and indexing strategies to ensure efficient data retrieval.
  • Collaborate with Data Experts
    • Work closely with data scientists to provide data in the right formats for machine learning and advanced analytics.
    • Collaborate with platform engineers to follow best practices and escalate common needs.
    • Support data analysts with SQL queries, views, and report generation, and assist in deploying machine learning models to production.
  • Ensure Security & Compliance
    • Implement role-based access controls, data encryption (both at-rest and in-transit), and adhere to industry and organizational data standards.
    • Regularly audit data access and usage to ensure compliance with privacy regulations and best practices.
  • Manage Infrastructure & Configuration
    • Set up and maintain Azure cloud infrastructure, including configuring Azure Data Lake Storage, Blob Storage, and deploying Databricks clusters.
    • Implement and manage data pipelines using Azure Data Factory and troubleshoot infrastructure-related issues as they arise.
  • Document & Train
    • Onboard new team members by providing access and initial training on tools.
    • Create comprehensive documentation and knowledge bases for data pipelines, best practices, and tooling.
  • Drive Continuous Improvement
    • Stay updated with the latest advancements in data engineering technologies.
    • Propose and implement workflow and system optimizations, and proactively identify areas for improvement and automation.
    • Keep the team informed on new features or changes in Azure, Databricks, or related technologies.

Requirements

  • Software Engineering & SQL: Python, SQL, software engineering practices, Python ecosystem, and SQL optimization.
  • Data Architecture: Design, integration, and cloud platform expertise, particularly with Azure and Databricks.
  • Data Processing with Big Data Frameworks: Mastery of PySpark and understanding of Delta Lake.
  • Data Storage & Data Management: Database management, data formats, and storage optimization.
  • Data Integration Tools: Proficiency with Azure Data Factory and DBT for data transformation.
  • Performance Optimization: Query tuning and pipeline optimization.
  • Security & Compliance: Data security, access control, and compliance with regulations.
  • DevOps & Automation: CI/CD, infrastructure as code, and basic knowledge of containerization.
  • Monitoring & Troubleshooting: Familiarity with logging, monitoring tools, and debugging skills.

What We Offer

  • Collaborative and Innovative Environment: Work in a team that values creativity and teamwork.
  • Certified Training and Personalized Support: Access to professional development and mentoring to enhance your skills.
  • Remote Work and Flexible Hours: Balance your work and personal life with our flexible working arrangements.
  • Competitive Compensation and Attractive Benefits: Enjoy a rewarding salary package with comprehensive benefits.
  • Mobility Opportunities: Possibility of relocation to Lille, Lyon, or Aix-en-Provence.

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