3 дня назад
Data Solutions Architect (Azure/AWS)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Solutions Architect (Azure/AWS): Designing and implementing enterprise-scale data platforms, Lakehouse and Data Warehouse architectures, and resilient batch and real-time pipelines across Azure, AWS, and multi-cloud environments with an accent on scalability, security, governance, and performance. Focus on architecting PySpark, Databricks, Kafka, Snowflake, and cloud-native data ecosystems, automating infrastructure with Terraform and CI/CD, and supporting analytics and AI/ML workloads.
Location: Remote, U.S.-based; hybrid options available
Company
is a technology and professional services firm established in 2004, specializing in innovative technologies and technology management services.
What you will do
- Define enterprise data platform strategies, architectural blueprints, and engineering standards.
- Design scalable Lakehouse and Data Warehouse architectures for structured and unstructured data.
- Architect resilient batch and real-time pipelines using PySpark, Databricks, Kafka, and cloud-native services.
- Integrate Azure and AWS data services, including Azure Data Factory, ADLS Gen2, Azure Synapse Analytics, Snowflake, and AWS services.
- Establish data governance, metadata management, data quality, observability, and security frameworks.
- Automate cloud infrastructure with Terraform and CI/CD, and integrate Power BI for enterprise reporting.
Requirements
- 10 or more years of experience in data engineering, data platform architecture, and enterprise software delivery.
- 5 or more years of experience architecting modern cloud data platforms on Azure, AWS, or multi-cloud environments.
- Hands-on experience with Azure Databricks, Azure Data Factory, ADLS Gen2, and Azure Synapse Analytics.
- Expertise in Lakehouse and Data Warehouse design using Snowflake and Databricks.
- Experience with PySpark, SQL, Apache Kafka, dimensional modeling, schema design, and query optimization.
- Proficiency in data governance, automated data quality validation, Terraform, and CI/CD automation.
Nice to have
- Experience supporting machine learning, advanced analytics, and AI/ML workloads.
- Hands-on experience with AWS Glue, AWS Lambda, and S3.
- Advanced Power BI and semantic layer modeling experience.
- Relevant Azure, Databricks, or Snowflake certifications.
Culture & Benefits
- Remote work for U.S.-based employees with hybrid options available.
- Opportunity to collaborate with engineering, analytics, business, and executive stakeholders.
- Responsibility for mentoring data engineers and establishing engineering best practices.
- Competitive salary.
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