Technical Lead - Cloud & Data Engineering

i2e Consulting
United States
3 months ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source

Tech stack

Sql Data Warehouse Artificial Intelligence Amazon Web Services Amazon S3 Microsoft Azure Cloud Computing Cloud Database Databases Information Engineering Extract Transform Load (ETL) Data Transformation Software Design Documents
+15 more
Python (Programming Language) Software Tools Cloud Services Azure Data Factory Snowflake Apache Spark Electronic Medical Records Usage Tracking Pyspark Information Technology AWS Glue Real Time Data Dataiku Data Pipelines Alteryx

Job description

We seek professionals who combine strong Pharma/Lifesciences domain expertise with an AI-ready mindset, leveraging AI, GenAI, Data, and Digital Technologies to transform business processes, accelerate outcomes, and unlock new opportunities for innovation., * Handle large, complex, multi-dimensional datasets, including structured, unstructured, and real-time data.

  • Develop complex data transformation ETLs using Python, PySpark, and Apache Spark.
  • Utilize cloud services from both AWS and Azure related to the data domain, demonstrating a strong understanding of their respective ecosystems.
  • Have a solid understanding of On-Prem/Cloud Data warehouse databases and their architecture.
  • Provide technical leadership, leading and delivering projects independently while ensuring high-quality results.
  • Stay updated with emerging trends in data tools, analysis techniques, and data usage, understanding their potential impact.
  • Understand the concepts and principles of data modelling and create, maintain, and update relevant data models for specific business needs.
  • Possess knowledge of cloud data engineering tools/components/technologies from both AWS and Azure, such as AWS Glue, EMR, Azure Data Factory, etc.
  • Have an additional advantage with knowledge of Snowflake, Dataiku, Alteryx, or similar technologies.
  • Collaborate effectively with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand requirements and deliver optimal data engineering solutions.
  • Ensure the scalability, reliability, and efficiency of data pipelines and processes.
  • Troubleshoot and resolve issues related to data engineering, performance, and scalability.
  • Document and maintain clear and comprehensive technical specifications, design documents, and best practices.
  • Manage and mentor team members, offering advice and assistance.
  • Collaborate with team members to complete tasks and achieve project objectives.

Requirements

Do you have experience in Technical writing?, Do you have a Bachelor’s degree?, A Bachelor’s Degree in Computer Science, or a similar discipline (or comparable practical experience) is required., As the Technical Lead Cloud & Data Engineering, you will be responsible for handling large, complex, multi-dimensional datasets, including structured, unstructured, and real-time data. You will develop complex data transformation ETLs and work extensively with Python, PySpark, Apache Spark, as well as cloud services from both AWS and Azure. Additionally, you will demonstrate strong expertise in cloud services related to the data domain and have a solid understanding of On-Prem/Cloud Data warehouse databases. You will also exhibit technical leadership capabilities, leading and delivering projects independently., * Experience - 5+ years

  • A Bachelor’s Degree in Computer Science, or a similar discipline (or comparable practical experience) is required.
  • Extensive experience in handling large, complex, multi-dimensional datasets, including structured, unstructured, and real-time data.
  • Strong experience in developing complex data transformation ETLs using Python, PySpark, and Apache Spark.
  • In-depth understanding of cloud services from both AWS and Azure related to the data domain, such as AWS Glue, EMR, S3, Athena, Azure Data Factory, etc.
  • Solid understanding of On-Prem/Cloud Data warehouse databases and their architecture.
  • Demonstrated technical leadership capabilities, with the ability to lead and deliver projects independently.
  • Up-to-date knowledge of emerging trends in data tools, analysis techniques, and data usage.
  • Ability to guide and develop team members through strong leadership and mentoring skills.
  • Communication skills that are effective in conveying complicated design concepts.

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