Solution Designer
3 weeks ago
Responsibilities :
1.
Architectural Design : Design end-to-end data solutions using Databricks platform, considering scalability, performance, security, and reliability requirements.
2.
Data Modeling : Define data models, schemas, and structures to support efficient data processing, storage, and retrieval within Databricks environment.
3.
Data Ingestion : Implement data ingestion pipelines from various sources such as databases, streaming platforms, and external APIs into Databricks for analytics and processing.
4.
Data Transformation : Develop data transformation pipelines using Apache Spark and Databricks notebooks to clean, transform, and enrich raw data into meaningful insights.
5.
Data Governance : Implement data governance policies, access controls, and data lineage tracking mechanisms within Databricks to ensure data quality, compliance, and auditability.
6.
Performance Optimization : Optimize data processing workflows, queries, and jobs within Databricks to achieve optimal performance and resource utilization.
7.
Integration : Integrate Databricks with other data platforms, tools, and services within the data ecosystem to enable seamless data flows and interoperability.
8.
Documentation : Document solution designs, data flows, architectural decisions, and best practices for Databricks usage to facilitate knowledge sharing and collaboration within the team.
9.
Collaboration : Collaborate with data engineers, data scientists, business analysts, and stakeholders to understand requirements, design solutions, and deliver value-added insights.
Qualifications :
1.
Bachelor's degree in Computer Science, Information Technology, or related field.
2.
Proven experience as a Solution Designer or Data Engineer with expertise in Databricks platform.
3.
Deep understanding of big data technologies, distributed computing, and data engineering principles.
4.
Hands-on experience with Apache Spark, Scala/Python programming languages, and Databricks notebooks.
5.
Familiarity with cloud-based data platforms such as Azure Databricks, AWS EMR
6.
Experience in data modeling, ETL/ELT processes, and data integration techniques.
7.
Knowledge of data governance, security, and compliance practices in data management.
8.
Strong analytical, problem-solving, and communication skills.
RequirementsWe are seeking a talented 10+ years Solution Designer with expertise in Databricks to join our team. The ideal candidate will have a strong background in designing and implementing data solutions using Databricks platform. This role requires a deep understanding of data engineering principles, and cloud-based analytics. As a Solution Designer, you will play a key role in architecting and implementing scalable, efficient, and high-performance data solutions. Responsibilities: 1. Architectural Design: Design end-to-end data solutions using Databricks platform, considering scalability, performance, security, and reliability requirements. 2. Data Modeling: Define data models, schemas, and structures to support efficient data processing, storage, and retrieval within Databricks environment. 3. Data Ingestion: Implement data ingestion pipelines from various sources such as databases, streaming platforms, and external APIs into Databricks for analytics and processing. 4. Data Transformation: Develop data transformation pipelines using Apache Spark and Databricks notebooks to clean, transform, and enrich raw data into meaningful insights. 5. Data Governance: Implement data governance policies, access controls, and data lineage tracking mechanisms within Databricks to ensure data quality, compliance, and auditability. 6. Performance Optimization: Optimize data processing workflows, queries, and jobs within Databricks to achieve optimal performance and resource utilization. 7. Integration: Integrate Databricks with other data platforms, tools, and services within the data ecosystem to enable seamless data flows and interoperability. 8. Documentation: Document solution designs, data flows, architectural decisions, and best practices for Databricks usage to facilitate knowledge sharing and collaboration within the team. 9. Collaboration: Collaborate with data engineers, data scientists, business analysts, and stakeholders to understand requirements, design solutions, and deliver value-added insights. Qualifications: 1. Bachelor's degree in Computer Science, Information Technology, or related field. 2. Proven experience as a Solution Designer or Data Engineer with expertise in Databricks platform. 3. Deep understanding of big data technologies, distributed computing, and data engineering principles. 4. Hands-on experience with Apache Spark, Scala/Python programming languages, and Databricks notebooks. 5. Familiarity with cloud-based data platforms such as Azure Databricks, AWS EMR 6. Experience in data modeling, ETL/ELT processes, and data integration techniques. 7. Knowledge of data governance, security, and compliance practices in data management. 8. Strong analytical, problem-solving, and communication skills. 9. Ability to work collaboratively in a cross-functional team environment and drive results
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