Data Engineering Lead

1 month ago


Noida, Uttar Pradesh, India DMI Full time

DMI is seeking a highly skilled Director of Data Engineering to support our manufacturing clients' large-scale digital transformation. The ideal candidate will have a proven track record of leading data engineering teams and driving successful project delivery.


Key Responsibilities:



  • Lead a distributed team of data engineers, focusing on resource management, team assignments, and career growth.
  • Contribute to the hiring process for team members in India.
  • Ensure compliance with best practices for data availability and security.
  • Apply strong communication and problem-solving skills to resolve data issues.
  • Develop and maintain expertise in abstract development frameworks.
  • Demonstrate accountability for assigned work and timelines.
  • Showcase leadership and technical competence.
  • Deliver assigned tasks on time and communicate project status effectively.

Requirements:



  • 8+ years of experience in management roles, with a focus on resourcing and employee growth.
  • 20+ years of experience or equivalent degree and experience.
  • Strong analytical and problem-solving skills, with expertise in data patterns and root cause analysis.
  • Familiarity with the data, analytics, and BI space, including Power BI.
  • Experience with Microsoft data integration platforms, such as Azure Data Factory, SSIS, and Synapse.
  • Experience with SQL and Python.
  • Familiarity with Azure DevOps and data management concepts.
  • Excellent written and verbal communication skills, with experience in delivering presentations.
  • Desirable skills: experience with cloud services (Azure), onshore client work, and helpdesk tools.

Preferred Experience:


Estimating and planning, data pipelines, data transformations, code and unit testing, PR and code reviews, performance and load testing, functional and regression testing, tier 2 support and consulting, production support, functional ask to technical design, data engineering, agile methodologies, CI/CD, metadata driven frameworks, technical documentation, Azure Synapse Spark, Python, complex SQL, Parquet and Delta file processing, ETL optimizations, and Azure DevOps.



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