Azure Data Architect
Pune City, India
Fulcrum Digital
Fulcrum Digital is at the forefront of digital transformation services, offering advanced digital engineering and acceleration solutions to drive business growth- Data
Architecture Design:
- Develop
and maintain the overall data architecture blueprint, incorporating data
warehousing, data lakehouse, and data modeling principles.
- Design
and implement data solutions leveraging the medallion architecture
(Bronze, Silver, Gold layers) for efficient data processing and quality
management.
- Define
data storage strategies, including the selection and configuration of
appropriate Azure services such as Azure Data Lake Storage (ADLS) Gen2,
Azure Synapse Analytics, Azure SQL Database, and NoSQL databases.
- Design
scalable and high-performance data pipelines for batch and real-time data
ingestion, transformation, and loading using Azure Data Factory (ADF) or
Azure Databricks.
- Establish
data governance frameworks, including data quality rules, metadata
management, data lineage, and security policies using Azure Purview or
similar tools.
- Define
and implement data retention and archival strategies.
- Ensure
compliance with relevant data regulations and security standards.
- Data
Modeling:
- Develop
conceptual, logical, and physical data models optimized for various use
cases, including analytical reporting, business intelligence, and machine
learning.
- Apply
different data modeling techniques such as relational modeling (e.g.,
star schema, snowflake schema), dimensional modeling, and potentially
Data Vault modeling based on requirements.
- Ensure
data models are scalable, maintainable, and aligned with business needs.
- Azure
Data Platform Expertise:
- Demonstrate
deep expertise in a wide range of Azure data services, including but not
limited to:
- Storage: Azure Data Lake Storage Gen2, Azure Blob Storage.
- Data
Processing: Azure Data Factory, Azure Databricks (PySpark, Spark
SQL), Azure Stream Analytics, Azure Synapse Pipelines.
- Data
Warehousing: Azure Synapse Analytics (Dedicated SQL Pools,
Serverless SQL Pools), Azure SQL Database.
- NoSQL
Databases: Azure Cosmos DB.
- Data
Governance: Azure Purview.
- Orchestration: Azure Logic Apps, Azure Functions.
- Monitoring: Azure Monitor, Azure Log Analytics.
- Architect
and implement solutions for data integration across diverse data sources,
both on-premises and in the cloud.
- Optimize
Azure data services for performance, cost-efficiency, and scalability.
- Implement
security best practices for Azure data services, including access
control, encryption, and network security.
- Collaboration
and Leadership:
- Collaborate
effectively with cross-functional teams, including data engineers, data
scientists, business analysts, and business stakeholders, to understand
data requirements and deliver solutions.
- Provide
technical guidance and mentorship to data engineers and other team
members.
- Lead
the evaluation and adoption of new Azure data technologies and services.
- Communicate
complex technical concepts clearly and effectively to both technical and
non-technical audiences.
- Participate
in the development of data standards and best practices.
- Problem
Solving and Innovation:
- Troubleshoot
and resolve complex data-related issues.
- Stay
up-to-date with the latest trends and advancements in data architecture,
data management, and cloud technologies.
- Identify
opportunities for innovation and improvement in our data platform and
processes.
Qualifications:
- Bachelor's
or Master's degree in Computer Science, Data Science, Information
Technology, or a related field.
- Minimum
of 8 years of experience in data warehousing, data modeling, and data
architecture.
- Minimum
of 4 years of hands-on experience designing and implementing data
solutions on Microsoft Azure.
- Strong
understanding of data warehousing concepts, principles, and best
practices.
- In-depth
knowledge of data lakehouse architectures and their benefits.
- Proven
experience in implementing the medallion architecture for data management.
- Excellent
data modeling skills, including conceptual, logical, and physical model
design.
- Proficiency
in SQL and experience with various database systems (relational and
NoSQL).
- Hands-on
experience with Azure data services such as ADLS Gen2, ADF, Azure
Databricks, Azure Synapse Analytics, Azure SQL Database, and Azure
Purview.
- Experience
with data integration tools and techniques.
- Strong
understanding of data governance, data quality, and data security
principles.
- Excellent
analytical, problem-solving, and communication skills.
- Ability
to work independently and collaboratively in a fast-paced environment.
Preferred Qualifications:
- Azure
Data Engineer Associate or Azure Solutions Architect Expert certification.
- Experience
with big data technologies (e.g., Hadoop, Spark).
- Familiarity
with data science and machine learning workflows.
- Experience
with DevOps practices and CI/CD pipelines for data solutions.
- Knowledge
of Python or other programming languages relevant to data engineering.
- Experience
with data visualization tools (e.g., Power BI, Tableau).
Requirements
- Data
Architecture Design:
- Develop
and maintain the overall data architecture blueprint, incorporating data
warehousing, data lakehouse, and data modeling principles.
- Design
and implement data solutions leveraging the medallion architecture
(Bronze, Silver, Gold layers) for efficient data processing and quality
management.
- Define
data storage strategies, including the selection and configuration of
appropriate Azure services such as Azure Data Lake Storage (ADLS) Gen2,
Azure Synapse Analytics, Azure SQL Database, and NoSQL databases.
- Design
scalable and high-performance data pipelines for batch and real-time data
ingestion, transformation, and loading using Azure Data Factory (ADF) or
Azure Databricks.
- Establish
data governance frameworks, including data quality rules, metadata
management, data lineage, and security policies using Azure Purview or
similar tools.
- Define
and implement data retention and archival strategies.
- Ensure
compliance with relevant data regulations and security standards.
- Data
Modeling:
- Develop
conceptual, logical, and physical data models optimized for various use
cases, including analytical reporting, business intelligence, and machine
learning.
- Apply
different data modeling techniques such as relational modeling (e.g.,
star schema, snowflake schema), dimensional modeling, and potentially
Data Vault modeling based on requirements.
- Ensure
data models are scalable, maintainable, and aligned with business needs.
- Azure
Data Platform Expertise:
- Demonstrate
deep expertise in a wide range of Azure data services, including but not
limited to:
- Storage: Azure Data Lake Storage Gen2, Azure Blob Storage.
- Data
Processing: Azure Data Factory, Azure Databricks (PySpark, Spark
SQL), Azure Stream Analytics, Azure Synapse Pipelines.
- Data
Warehousing: Azure Synapse Analytics (Dedicated SQL Pools,
Serverless SQL Pools), Azure SQL Database.
- NoSQL
Databases: Azure Cosmos DB.
- Data
Governance: Azure Purview.
- Orchestration: Azure Logic Apps, Azure Functions.
- Monitoring: Azure Monitor, Azure Log Analytics.
- Architect
and implement solutions for data integration across diverse data sources,
both on-premises and in the cloud.
- Optimize
Azure data services for performance, cost-efficiency, and scalability.
- Implement
security best practices for Azure data services, including access
control, encryption, and network security.
- Collaboration
and Leadership:
- Collaborate
effectively with cross-functional teams, including data engineers, data
scientists, business analysts, and business stakeholders, to understand
data requirements and deliver solutions.
- Provide
technical guidance and mentorship to data engineers and other team
members.
- Lead
the evaluation and adoption of new Azure data technologies and services.
- Communicate
complex technical concepts clearly and effectively to both technical and
non-technical audiences.
- Participate
in the development of data standards and best practices.
- Problem
Solving and Innovation:
- Troubleshoot
and resolve complex data-related issues.
- Stay
up-to-date with the latest trends and advancements in data architecture,
data management, and cloud technologies.
- Identify
opportunities for innovation and improvement in our data platform and
processes.
Qualifications:
- Bachelor's
or Master's degree in Computer Science, Data Science, Information
Technology, or a related field.
- Minimum
of 8 years of experience in data warehousing, data modeling, and data
architecture.
- Minimum
of 4 years of hands-on experience designing and implementing data
solutions on Microsoft Azure.
- Strong
understanding of data warehousing concepts, principles, and best
practices.
- In-depth
knowledge of data lakehouse architectures and their benefits.
- Proven
experience in implementing the medallion architecture for data management.
- Excellent
data modeling skills, including conceptual, logical, and physical model
design.
- Proficiency
in SQL and experience with various database systems (relational and
NoSQL).
- Hands-on
experience with Azure data services such as ADLS Gen2, ADF, Azure
Databricks, Azure Synapse Analytics, Azure SQL Database, and Azure
Purview.
- Experience
with data integration tools and techniques.
- Strong
understanding of data governance, data quality, and data security
principles.
- Excellent
analytical, problem-solving, and communication skills.
- Ability
to work independently and collaboratively in a fast-paced environment.
Preferred Qualifications:
- Azure
Data Engineer Associate or Azure Solutions Architect Expert certification.
- Experience
with big data technologies (e.g., Hadoop, Spark).
- Familiarity
with data science and machine learning workflows.
- Experience
with DevOps practices and CI/CD pipelines for data solutions.
- Knowledge
of Python or other programming languages relevant to data engineering.
- Experience
with data visualization tools (e.g., Power BI, Tableau).
Benefits
- Data
Architecture Design:
- Develop
and maintain the overall data architecture blueprint, incorporating data
warehousing, data lakehouse, and data modeling principles.
- Design
and implement data solutions leveraging the medallion architecture
(Bronze, Silver, Gold layers) for efficient data processing and quality
management.
- Define
data storage strategies, including the selection and configuration of
appropriate Azure services such as Azure Data Lake Storage (ADLS) Gen2,
Azure Synapse Analytics, Azure SQL Database, and NoSQL databases.
- Design
scalable and high-performance data pipelines for batch and real-time data
ingestion, transformation, and loading using Azure Data Factory (ADF) or
Azure Databricks.
- Establish
data governance frameworks, including data quality rules, metadata
management, data lineage, and security policies using Azure Purview or
similar tools.
- Define
and implement data retention and archival strategies.
- Ensure
compliance with relevant data regulations and security standards.
- Data
Modeling:
- Develop
conceptual, logical, and physical data models optimized for various use
cases, including analytical reporting, business intelligence, and machine
learning.
- Apply
different data modeling techniques such as relational modeling (e.g.,
star schema, snowflake schema), dimensional modeling, and potentially
Data Vault modeling based on requirements.
- Ensure
data models are scalable, maintainable, and aligned with business needs.
- Azure
Data Platform Expertise:
- Demonstrate
deep expertise in a wide range of Azure data services, including but not
limited to:
- Storage: Azure Data Lake Storage Gen2, Azure Blob Storage.
- Data
Processing: Azure Data Factory, Azure Databricks (PySpark, Spark
SQL), Azure Stream Analytics, Azure Synapse Pipelines.
- Data
Warehousing: Azure Synapse Analytics (Dedicated SQL Pools,
Serverless SQL Pools), Azure SQL Database.
- NoSQL
Databases: Azure Cosmos DB.
- Data
Governance: Azure Purview.
- Orchestration: Azure Logic Apps, Azure Functions.
- Monitoring: Azure Monitor, Azure Log Analytics.
- Architect
and implement solutions for data integration across diverse data sources,
both on-premises and in the cloud.
- Optimize
Azure data services for performance, cost-efficiency, and scalability.
- Implement
security best practices for Azure data services, including access
control, encryption, and network security.
- Collaboration
and Leadership:
- Collaborate
effectively with cross-functional teams, including data engineers, data
scientists, business analysts, and business stakeholders, to understand
data requirements and deliver solutions.
- Provide
technical guidance and mentorship to data engineers and other team
members.
- Lead
the evaluation and adoption of new Azure data technologies and services.
- Communicate
complex technical concepts clearly and effectively to both technical and
non-technical audiences.
- Participate
in the development of data standards and best practices.
- Problem
Solving and Innovation:
- Troubleshoot
and resolve complex data-related issues.
- Stay
up-to-date with the latest trends and advancements in data architecture,
data management, and cloud technologies.
- Identify
opportunities for innovation and improvement in our data platform and
processes.
Qualifications:
- Bachelor's
or Master's degree in Computer Science, Data Science, Information
Technology, or a related field.
- Minimum
of 8 years of experience in data warehousing, data modeling, and data
architecture.
- Minimum
of 4 years of hands-on experience designing and implementing data
solutions on Microsoft Azure.
- Strong
understanding of data warehousing concepts, principles, and best
practices.
- In-depth
knowledge of data lakehouse architectures and their benefits.
- Proven
experience in implementing the medallion architecture for data management.
- Excellent
data modeling skills, including conceptual, logical, and physical model
design.
- Proficiency
in SQL and experience with various database systems (relational and
NoSQL).
- Hands-on
experience with Azure data services such as ADLS Gen2, ADF, Azure
Databricks, Azure Synapse Analytics, Azure SQL Database, and Azure
Purview.
- Experience
with data integration tools and techniques.
- Strong
understanding of data governance, data quality, and data security
principles.
- Excellent
analytical, problem-solving, and communication skills.
- Ability
to work independently and collaboratively in a fast-paced environment.
Preferred Qualifications:
- Azure
Data Engineer Associate or Azure Solutions Architect Expert certification.
- Experience
with big data technologies (e.g., Hadoop, Spark).
- Familiarity
with data science and machine learning workflows.
- Experience
with DevOps practices and CI/CD pipelines for data solutions.
- Knowledge
of Python or other programming languages relevant to data engineering.
- Experience
with data visualization tools (e.g., Power BI, Tableau).
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
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Category:
Architecture Jobs
Tags: Architecture Azure Big Data Business Intelligence CI/CD Computer Science Cosmos DB Databricks Data governance Data management Data pipelines Data quality Data visualization Data Warehousing DevOps Engineering Hadoop Machine Learning Model design NoSQL Pipelines Power BI PySpark Python Security Snowflake Spark SQL Tableau
Perks/benefits: Career development
Region:
Asia/Pacific
Country:
India
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