What are the responsibilities and job description for the Architect - Lead position at Careers Integrated Resources Inc?
Job Description: GT Title: Niche Architect - Lead
We are seeking a highly skilled Cloud Data Architect to design, implement, and optimize comprehensive data warehousing solutions on the cloud, with a strong focus on Databricks Lakehouse. The ideal candidate will possess a deep understanding of cloud architecture, data warehousing principles, dimensional modeling, and big data technologies. This role requires strategic thinking, technical expertise, and the ability to collaborate with cross-functional teams translate business & non-functional requirements into data model for analytics and technical solution aligned with technology strategy. It would include dimensional models, data flows and other solution details to ensure data integrity, performance, and scalability while aligning with business objectives.
Key Responsibilities:
1. Strategic Data Architecture:
- Develop and maintain the data and solution architecture for robust, scalable, and secure cloud-based data warehousing solutions, including Databricks Lakehouse.
- Lead the strategic design of data models, schemas, and data flows to support enterprise business intelligence and advanced analytics needs.
- Ensure the architecture aligns with business goals, delivering high availability, disaster recovery, and security.
2. Solution Implementation and Management:
- Oversee the implementation of comprehensive data warehousing solutions using cloud data platforms and Databricks Lakehouse.
- Architect and implement ETL/ELT processes for efficient data ingestion, transformation, and loading, particularly within the Databricks environment.
- Optimize the performance of data warehouses and Lakehouse solutions to handle large-scale data processing and complex data consumption patterns.
- Design and implement operation observability, deliver operational metrics for data products.
3. Technical Leadership and Collaboration:
- Act as a subject matter expert and advisor to data engineers, analysts, and business stakeholders.
- Lead and mentor technical teams in best practices, architectural standards, and emerging technologies.
- Communicate and present architecture solutions and strategies to both technical and non-technical stakeholders.
4. Continuous Innovation and Improvement:
- Stay abreast of the latest advancements in cloud technologies, data warehousing, and Databricks Lakehouse architecture.
- Conduct regular performance tuning, capacity planning, and cost optimization.
- Implement robust data governance, quality, and compliance measures to maintain data integrity and security.
Skills and Qualifications:
1. Technical Expertise:
- Cloud Data Analytics Platforms: Deep expertise designing data architecture and solutions architecture using Lakehouse pattern in cloud platforms such as Databricks, AWS, Google Cloud Platform, or Microsoft Azure. AWS preferred.
- Data Warehousing: Advanced proficiency in cloud-based data warehousing technologies (e.g. Databricks, AWS Redshift, Snowflake, BigQuery, etc ) and Databricks Lakehouse.
- ETL/ELT Tools: Strong experience with ETL/ELT tools like Databricks DLT, Spark based ETL, etc
- Database Management: Strong knowledge of SQL and Lakehouse databases, with expertise in logical and dimensional data modeling, schema design, and normalization/denormalization techniques.
2. Analytical and Strategic Thinking:
- Strong analytical and problem-solving skills to diagnose issues and design innovative solutions.
- Ability to analyze complex business requirements and translate them into scalable and efficient technical specifications.
3. Leadership and Soft Skills:
- Excellent leadership, communication, and interpersonal skills to effectively collaborate with cross-functional teams and stakeholders.
- Strong project management skills to oversee multiple projects, ensure timely delivery, and meet organizational goals.
- Ability to work independently and lead teams in a fast-paced, dynamic environment.
Experience:
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
- Minimum of 10 years of experience in data warehousing, with at least 5 years in cloud environments.
- Proven track record of designing and implementing complex cloud data warehousing solutions, including extensive experience with Databricks Lakehouse.
5. Certifications (Preferred):
- AWS Certified Solutions Architect
- AWS Certified Data Engineer
- Databricks Certification (e.g., Databricks Certified Data Engineer Associate/Professional)
Comments for Suppliers: Please refer to Job Description.
Summary:
Data & Analytics solution architect for Databricks Lakehouse implementation with strong data modeling and hands-on expertise.
Skills :
Data model design for datawarehouses
Dimensional Modeling
Data modeling for Lakehouse architecture
Strong SQL skills
Experience with Cloud Lakehouse/Datawarehouse technologies such as Databricks, Snowflake or AWS Redshift
Notes:
- Team sits in EST. Please make sure candidates are comfortable working CST/EST hours - Manager stated they could be flexible on time zones for right fit as well
Interviews:
- Screening call with a team member
- 2nd round: Presenting past work to Manager. Will need to speak on thought and decision making process.
We are seeking a highly skilled Cloud Data Architect to design, implement, and optimize comprehensive data warehousing solutions on the cloud, with a strong focus on Databricks Lakehouse. The ideal candidate will possess a deep understanding of cloud architecture, data warehousing principles, dimensional modeling, and big data technologies. This role requires strategic thinking, technical expertise, and the ability to collaborate with cross-functional teams translate business & non-functional requirements into data model for analytics and technical solution aligned with technology strategy. It would include dimensional models, data flows and other solution details to ensure data integrity, performance, and scalability while aligning with business objectives.
Key Responsibilities:
1. Strategic Data Architecture:
- Develop and maintain the data and solution architecture for robust, scalable, and secure cloud-based data warehousing solutions, including Databricks Lakehouse.
- Lead the strategic design of data models, schemas, and data flows to support enterprise business intelligence and advanced analytics needs.
- Ensure the architecture aligns with business goals, delivering high availability, disaster recovery, and security.
2. Solution Implementation and Management:
- Oversee the implementation of comprehensive data warehousing solutions using cloud data platforms and Databricks Lakehouse.
- Architect and implement ETL/ELT processes for efficient data ingestion, transformation, and loading, particularly within the Databricks environment.
- Optimize the performance of data warehouses and Lakehouse solutions to handle large-scale data processing and complex data consumption patterns.
- Design and implement operation observability, deliver operational metrics for data products.
3. Technical Leadership and Collaboration:
- Act as a subject matter expert and advisor to data engineers, analysts, and business stakeholders.
- Lead and mentor technical teams in best practices, architectural standards, and emerging technologies.
- Communicate and present architecture solutions and strategies to both technical and non-technical stakeholders.
4. Continuous Innovation and Improvement:
- Stay abreast of the latest advancements in cloud technologies, data warehousing, and Databricks Lakehouse architecture.
- Conduct regular performance tuning, capacity planning, and cost optimization.
- Implement robust data governance, quality, and compliance measures to maintain data integrity and security.
Skills and Qualifications:
1. Technical Expertise:
- Cloud Data Analytics Platforms: Deep expertise designing data architecture and solutions architecture using Lakehouse pattern in cloud platforms such as Databricks, AWS, Google Cloud Platform, or Microsoft Azure. AWS preferred.
- Data Warehousing: Advanced proficiency in cloud-based data warehousing technologies (e.g. Databricks, AWS Redshift, Snowflake, BigQuery, etc ) and Databricks Lakehouse.
- ETL/ELT Tools: Strong experience with ETL/ELT tools like Databricks DLT, Spark based ETL, etc
- Database Management: Strong knowledge of SQL and Lakehouse databases, with expertise in logical and dimensional data modeling, schema design, and normalization/denormalization techniques.
2. Analytical and Strategic Thinking:
- Strong analytical and problem-solving skills to diagnose issues and design innovative solutions.
- Ability to analyze complex business requirements and translate them into scalable and efficient technical specifications.
3. Leadership and Soft Skills:
- Excellent leadership, communication, and interpersonal skills to effectively collaborate with cross-functional teams and stakeholders.
- Strong project management skills to oversee multiple projects, ensure timely delivery, and meet organizational goals.
- Ability to work independently and lead teams in a fast-paced, dynamic environment.
Experience:
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
- Minimum of 10 years of experience in data warehousing, with at least 5 years in cloud environments.
- Proven track record of designing and implementing complex cloud data warehousing solutions, including extensive experience with Databricks Lakehouse.
5. Certifications (Preferred):
- AWS Certified Solutions Architect
- AWS Certified Data Engineer
- Databricks Certification (e.g., Databricks Certified Data Engineer Associate/Professional)
Comments for Suppliers: Please refer to Job Description.
Summary:
Data & Analytics solution architect for Databricks Lakehouse implementation with strong data modeling and hands-on expertise.
Skills :
Data model design for datawarehouses
Dimensional Modeling
Data modeling for Lakehouse architecture
Strong SQL skills
Experience with Cloud Lakehouse/Datawarehouse technologies such as Databricks, Snowflake or AWS Redshift
Notes:
- Team sits in EST. Please make sure candidates are comfortable working CST/EST hours - Manager stated they could be flexible on time zones for right fit as well
Interviews:
- Screening call with a team member
- 2nd round: Presenting past work to Manager. Will need to speak on thought and decision making process.
