CLOUD AMAZE - DW Architect (Practice)

HEXAWAREUnited States,
Hybrid

About The Position

We are seeking highly skilled and experienced Data Practice / Solution Architects to work onsite with our esteemed clients. The ideal candidates will have expertise in designing and implementing cutting-edge data solutions tailored to the client's specific needs. The roles require a deep understanding of cloud platforms, big data technologies, and data architecture principles. The architects will be responsible for driving end-to-end data strategies, ensuring scalability, performance, and reliability of data systems.

Requirements

  • Extensive experience with Apache Spark for big data processing and analytics.
  • Proficiency in Spark Core, Spark SQL, Spark Streaming, and MLlib.
  • Knowledge of distributed computing systems and frameworks.
  • Familiarity with Hadoop ecosystem components such as HDFS, Hive, and YARN.
  • Expertise in optimizing Spark jobs for performance and scalability.
  • Designing and implementing data platforms on Azure Cloud using Snowflake and Databricks
  • Five years of prior experience in modernizing and migrating legacy data platforms to cloud is a must have experience.
  • 10 - 15 years of experience in designing and implementing highly scalable data lakes, Lakehouse’s.
  • At least 5 years of experience financial domain
  • 3-5 years of experience with SEI Wealth Management must have experience.
  • 5 plus years of experience in creating data models.

Nice To Haves

  • Hands-on experience with Exadata is plus

Responsibilities

  • Collaborate with stakeholders to understand business requirements and translate them into technical solutions.
  • Design and implement scalable, secure, and high-performance data architectures.
  • Provide technical leadership and guidance to development teams.
  • Optimize data pipelines, storage, and processing frameworks for efficiency and cost-effectiveness.
  • Ensure data governance, security, and compliance standards are met.
  • Evaluate and recommend tools, technologies, and frameworks based on project needs.
  • Conduct performance tuning and troubleshooting of data systems.
  • Stay updated with emerging trends and technologies in cloud and big data ecosystems.
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