- Knowledge and experience in Lake house architecture .
- Strong knowledge & Experience in Snowflake.
- Experience in Azure storages(Data lake store gen2) & databases(Synapse , SqlDB & Cosmos)
- Experience in structure & semi structure(XML & Json) data ingestion.
- Design and develop endtoend data ingestion frameworks and solutions using Azure Cloud services, ensuring efficient and reliable data integration from various sources into our enterprise data ecosystem.
- Collaborate with business stakeholders, data scientists, data engineers, and software developers to understand data requirements and design the most suitable data ingestion strategies and architectures.
- Evaluate and select appropriate Azure Cloud services for data ingestion, including Azure Data Factory, Kafka , PySpark and others, based on project requirements.
- Define and implement data ingestion patterns and best practices, considering data governance, security, privacy, scalability, and performance requirements.
- Develop and maintain data pipeline orchestration and monitoring frameworks to ensure the smooth and reliable operation of data ingestion processes.
- Optimize data ingestion workflows and architectures to support realtime and batch processing of large volumes of data from diverse sources.
- Implement data quality checks, error handling, and data validation mechanisms within data ingestion systems to ensure data accuracy and integrity.
- Stay uptodate with the latest Azure Cloud technologies and industry trends related to data ingestion and recommend improvements and enhancements to existing processes.
- Collaborate with other data architects, database administrators, and infrastructure teams to ensure the integration of data ingestion systems with data storage, data processing, and data analytics solutions.
- Provide technical guidance and mentorship to data engineers and data integration teams, fostering knowledge sharing and promoting best practices.
- Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
- 8+ years of experience as a Data Architect or similar role, with expertise in data ingestion systems and Azure Cloud.
- Strong proficiency in Azure Cloud services and tools for data ingestion, such as Azure Data Factory, Azure Event Hubs, Azure Stream Analytics, Azure Logic Apps, and others.
- Proven experience in designing and implementing complex data ingestion frameworks and architectures for largescale enterprise environments.
- Indepth understanding of data ingestion patterns, data integration techniques, and best practices.
- Solid understanding of data governance, data security, and privacy requirements.
- Proficiency in programming languages such as Python, SQL, or Scala for data manipulation and transformation.
- Strong problemsolving and analytical skills, with the ability to architect and troubleshoot complex data ingestion systems.
- Excellent communication and collaboration skills to work effectively with crossfunctional teams and stakeholders.
- Relevant certifications in Azure Cloud and/or Data Engineering is a plus.
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EY - Data Architect - Azure/Data Ingestion - hyderabad, India - Ernst and Young LLP
Description
Job Description :
We are seeking a highly skilled and experienced Enterprise Data Architect with expertise in Azure Cloud and Data Ingestion Systems to join our team.
As an Enterprise Data Architect, you will play a crucial role in designing and implementing scalable and efficient data ingestion systems and strategies, leveraging Azure Cloud technologies.
Your expertise in Azure and data ingestion will be essential in ensuring seamless, reliable, and accurate data processing and integration across our enterprise.
Responsibilities :
Requirements :
If you are an experienced Enterprise Data Architect with expertise in Azure Cloud and Data Ingestion Systems, and have a passion for designing robust and scalable data integration solutions, we invite you to join our team.
We offer a challenging and dynamic work environment where you will have the opportunity to make a significant impact on our enterprise data ecosystem and contribute to the success of our data-driven initiatives.
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