Description:
Responsibilities :
- Work closely with business units to understand data requirements and translate them into actionable data pipelines and insights.
- Data visualization: Proficient in building dashboards and reports, delivering insightful data to stakeholders
- Data Modeling: Strong understanding of dimensional modeling, star and snowflake schemas, and best practices for analytics-ready tables.
- ETL/ELT: Experience with data ingestion tools and pipeline scheduling, including incremental loads and monitoring.
- Data Quality: Ability to implement dbt tests, data validation checks, and freshness monitoring.
- Version Control: Proficiency in Git fundamentals, including branch management and the code review process.
- Basic scripting skills for automation, data validation, and API integrations (Python or VS).
- Analytics Infrastructure: Understanding of data warehouse architecture, table design optimization, and cost control principles.
- Integrations: Create and manage connectors and data integrations between internal and external systems (CRM, ERP, WMS, Demand Planning Tool, Customer Portals’ etc).
- Optimize dataflows for performance, reusability, and scalability.
· Own governance, quality, and security standards across the data platform
Requirements:
Responsibilities :
- Work closely with business units to understand data requirements and translate them into actionable data pipelines and insights.
- Data visualization: Proficient in building dashboards and reports, delivering insightful data to stakeholders
- Data Modeling: Strong understanding of dimensional modeling, star and snowflake schemas, and best practices for analytics-ready tables.
- ETL/ELT: Experience with data ingestion tools and pipeline scheduling, including incremental loads and monitoring.
- Data Quality: Ability to implement dbt tests, data validation checks, and freshness monitoring.
- Version Control: Proficiency in Git fundamentals, including branch management and the code review process.
- Basic scripting skills for automation, data validation, and API integrations (Python or VS).
- Analytics Infrastructure: Understanding of data warehouse architecture, table design optimization, and cost control principles.
- Integrations: Create and manage connectors and data integrations between internal and external systems (CRM, ERP, WMS, Demand Planning Tool, Customer Portals’ etc).
- Optimize dataflows for performance, reusability, and scalability.
· Own governance, quality, and security standards across the data platform
Responsibilities :
- Work closely with business units to understand data requirements and translate them into actionable data pipelines and insights.
- Data visualization: Proficient in building dashboards and reports, delivering insightful data to stakeholders
- Data Modeling: Strong understanding of dimensional modeling, star and snowflake schemas, and best practices for analytics-ready tables.
- ETL/ELT: Experience with data ingestion tools and pipeline scheduling, including incremental loads and monitoring.
- Data Quality: Ability to implement dbt tests, data validation checks, and freshness monitoring.
- Version Control: Proficiency in Git fundamentals, including branch management and the code review process.
- Basic scripting skills for automation, data validation, and API integrations (Python or VS).
- Analytics Infrastructure: Understanding of data warehouse architecture, table design optimization, and cost control principles.
- Integrations: Create and manage connectors and data integrations between internal and external systems (CRM, ERP, WMS, Demand Planning Tool, Customer Portals’ etc).
- Optimize dataflows for performance, reusability, and scalability.
· Own governance, quality, and security standards across the data platform
- Work closely with business units to understand data requirements and translate them into actionable data pipelines and insights.
- Data visualization: Proficient in building dashboards and reports, delivering insightful data to stakeholders
- Data Modeling: Strong understanding of dimensional modeling, star and snowflake schemas, and best practices for analytics-ready tables.
- ETL/ELT: Experience with data ingestion tools and pipeline scheduling, including incremental loads and monitoring.
- Data Quality: Ability to implement dbt tests, data validation checks, and freshness monitoring.
- Version Control: Proficiency in Git fundamentals, including branch management and the code review process.
- Basic scripting skills for automation, data validation, and API integrations (Python or VS).
- Analytics Infrastructure: Understanding of data warehouse architecture, table design optimization, and cost control principles.
- Integrations: Create and manage connectors and data integrations between internal and external systems (CRM, ERP, WMS, Demand Planning Tool, Customer Portals’ etc).
- Optimize dataflows for performance, reusability, and scalability.
- Data Analyst: 3 to 4 years
- Dynamics CRM Or SAP B1, Or Similar CRM/ERP Platforms.
- Microsoft certifications (e.g., PL-300, PL-400) are advantageous.
- Microsoft certifications (e.g., PL-300, PL-400) are advantageous.
- 3–5 years of experience in data engineering, business intelligence, or analytics.
- Experience in Agile/Scrum development environments.
- Strong analytical thinking with a problem-solving mindset.
- Excellent communication and stakeholder engagement skills.
- Ability to manage multiple tasks in a fast-paced environment.
- Passion for clean, efficient, and well-documented code and data solutions.
- Exposure to retail or distribution data environments.
- Prior experience working with Dynamics CRM or SAP B1, or similar CRM/ERP platforms.
- Strong hands-on experience with Microsoft Dataverse, Dataflows, Power BI, and the Power Platform.
- Proficient in Power Query (M language), DAX, and data modeling best practices.
- Solid understanding of relational databases, data normalization, and schema design.
- Experience with REST APIs, connectors, and integration tools.
- Proficient in scripting skills for automation, data validation, and API integrations
- Knowledge and/or interest in AI and workflow automation tools is beneficial
- Microsoft certifications (e.g., PL-300, PL-400) are advantageous.
- Microsoft certifications (e.g., PL-300, PL-400) are advantageous.
- 3–5 years of experience in data engineering, business intelligence, or analytics.
- Experience in Agile/Scrum development environments.
- Strong analytical thinking with a problem-solving mindset.
- Excellent communication and stakeholder engagement skills.
- Ability to manage multiple tasks in a fast-paced environment.
- Passion for clean, efficient, and well-documented code and data solutions.
- Exposure to retail or distribution data environments.
- Prior experience working with Dynamics CRM or SAP B1, or similar CRM/ERP platforms.
- Strong hands-on experience with Microsoft Dataverse, Dataflows, Power BI, and the Power Platform.
- Proficient in Power Query (M language), DAX, and data modeling best practices.
- Solid understanding of relational databases, data normalization, and schema design.
- Experience with REST APIs, connectors, and integration tools.
- Proficient in scripting skills for automation, data validation, and API integrations
- Knowledge and/or interest in AI and workflow automation tools is beneficial
- Microsoft certifications (e.g., PL-300, PL-400) are advantageous.
- Microsoft certifications (e.g., PL-300, PL-400) are advantageous.
- 3–5 years of experience in data engineering, business intelligence, or analytics.
- Experience in Agile/Scrum development environments.
- Strong analytical thinking with a problem-solving mindset.
- Excellent communication and stakeholder engagement skills.
- Ability to manage multiple tasks in a fast-paced environment.
- Passion for clean, efficient, and well-documented code and data solutions.
- Exposure to retail or distribution data environments.
- Prior experience working with Dynamics CRM or SAP B1, or similar CRM/ERP platforms.
- Strong hands-on experience with Microsoft Dataverse, Dataflows, Power BI, and the Power Platform.
- Proficient in Power Query (M language), DAX, and data modeling best practices.
- Solid understanding of relational databases, data normalization, and schema design.
- Experience with REST APIs, connectors, and integration tools.
- Proficient in scripting skills for automation, data validation, and API integrations
- Knowledge and/or interest in AI and workflow automation tools is beneficial
30 Apr 2025;
from:
careers24.com