Lead Data Engineer/ Data Architect

Enable Dataorporated

About The Position

Enable Data is seeking an experienced Azure Data Architect with strong hands-on engineering expertise to design, develop, optimize, and modernize enterprise-scale data platforms. The role combines solution architecture, technical leadership, and individual contributor responsibilities, requiring deep expertise in Azure data services, data engineering best practices, and large-scale data processing using PySpark, Python, SQL, and Azure Databricks. The ideal candidate will be responsible for analyzing existing data products and pipelines, identifying improvement opportunities, leading refactoring and redesign initiatives, and implementing scalable, reliable, and high-performance data solutions on Azure.

Requirements

  • Overall 15+ years of experience with 10+ years of experience in Data Engineering and Analytics solutions.
  • Strong hands-on experience in PySpark, Python, and SQL.
  • Expertise in Azure Databricks and Azure data ecosystem.
  • Experience designing and implementing scalable data architectures.
  • Ability to analyze, optimize, refactor, and redesign existing data pipelines.
  • Azure Data Lake, Azure Data Factory, Azure Synapse.
  • Data warehousing, lakehouse architecture, and cloud migration.
  • CI/CD, Git, and Agile development practices.

Responsibilities

  • Design end-to-end data architectures on Microsoft Azure.
  • Define data ingestion, transformation, storage, governance, and consumption strategies.
  • Create scalable, secure, and cost-effective data solutions aligned with business objectives.
  • Establish architectural standards, design patterns, and best practices for data engineering teams.
  • Collaborate with business stakeholders, product owners, and technical teams to translate requirements into technical solutions.
  • Design, develop, and modernize enterprise data platforms on Azure.
  • Analyze, refactor, and redesign existing data pipelines and products while building new scalable data solutions.
  • Act as a hands-on individual contributor with technical leadership responsibilities, including mentoring junior developers and driving best practices.
  • Develop and maintain ETL/ELT solutions and data products.
  • Performance tuning, troubleshooting, and data quality implementation.
  • Mentor and guide junior developers and conduct code reviews.
  • Collaborate with cross-functional teams to deliver end-to-end data solutions.
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