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Job Description

Automation

Title   

Data Architect

Type of Employment

Permanent

Overall Years of Experience

12-15 years

Relevant Years of Experience

10+

 

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

                

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