Data Architect

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Job Description

Title Data Architect Rank Assistant Director

Type of Employment Permanent

Overall Years of Experience 12-15 years Relevant Years of Experience 10+

Requisition Date Resource On-board Date

Data Architect

Data Architect is responsible for designing and implementing data architecture for multiple projects and also build strategies for data governance

Position Summary

• 12 – 15 yrs of experience in a similar profile with strong service delivery background
• Experience as a Data Architect with a focus on Spark and Data Lake technologies.
• Experience in Azure Synapse Analytics
• Proficiency in Apache Spark for large-scale data processing.
• Expertise in Databricks, Delta Lake, Azure data factory, and other cloud-based data services.
• Strong understanding of data modeling, ETL processes, and data warehousing principles.
• Implement a data governance framework with Unity Catalog .
• Knowledge in designing scalable streaming data pipeline using Azure Event Hub, Azure Stream analytics, Spark streaming
• Experience with SQL and NoSQL databases, as well as familiarity with big data file formats like Parquet and Avro.
• Hands on Experience in python and relevant libraries such as pyspark, numpy etc
• Knowledge of Machine Learning pipelines, GenAI, LLM will be plus
• Excellent analytical, problem-solving, and technical leadership skills.
• Experience in integration with business intelligence tools such as Power BI
• Effective communication and collaboration abilities
• Excellent interpersonal skills and a collaborative management style
• Own and delegate responsibilities effectively
• Ability to analyse and suggest solutions
• Strong command on verbal and written English language
  
  

Roles And Responsibilities

Essential

• Work as a Data Architect and able to design and implement data architecture for projects having complex data such as Big Data, Data lakes etc
• Work with the customers to define strategy for data architecture and data governance
• Guide the team to implement solutions around data engineering
• Proactively identify risks and communicate to stakeholders. Develop strategies to mitigate risks
• Build best practices to enable faster service delivery
• Build reusable components to reduce cost
• Build scalable and cost effective architecture
  
  

EY | Building a better working world

EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.

Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.

EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.

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