Data and Ai Architect
5 months ago
We are seeking an experienced Data and AI Architect to join our team. As a Data and AI Architect, you will be responsible for designing, developing, and implementing scalable data and AI solutions. You will work closely with cross-functional teams to understand business requirements and translate them into technical designs that leverage data and AI technologies. Your expertise in data architecture, machine learning, and cloud technologies will be crucial in guiding our organizations data-driven initiatives.
**Responsibilities**:
1. Collaborate with stakeholders to gather and analyze business requirements and translate them into data and AI architecture designs.
Design and develop end-to-end data and AI solutions, including data ingestion, storage, processing, analysis, and visualization.
Create and maintain data architecture blueprints, documenting data flows, data models, and data integration patterns.
Evaluate and recommend appropriate data and AI technologies, frameworks, and tools based on business requirements and industry best practices.
Lead and participate in data engineering and data science projects, providing technical guidance and mentoring to the team.
Ensure data solutions adhere to data governance, data security, and data privacy standards.
Collaborate with infrastructure teams to optimize data storage, processing, and retrieval performance.
Conduct performance tuning and optimization activities to ensure optimal utilization of data and AI solutions.
Provide thought leadership and contribute to the development of data and AI strategies, roadmaps, and best practices.
**Qualifications**:
1. Bachelors or masters degree in computer science, data science, or a related field.
Minimum of 8 years of professional experience in data engineering, data architecture, or related roles.
Strong expertise in data architecture design, data modeling, data integration, and data governance.
Proficiency in designing and implementing data pipelines, ETL/ELT processes, and data warehousing solutions.
Extensive experience with cloud platforms such as AWS, Azure, or Google Cloud, including services like S3, Redshift, BigQuery, etc.
Solid understanding of machine learning concepts, algorithms, and frameworks.
Hands-on experience with machine learning model development, training, and deployment.
Strong programming skills in languages like Python, Java, or Scala.
Familiarity with data visualization and reporting tools like Tableau, Power BI, or Qlik.
Excellent problem-solving and analytical skills.
Ability to work effectively in cross-functional teams and communicate complex technical concepts to non-technical stakeholders.
Strong leadership and mentoring abilities.
**Preferred Qualifications**:
1. Experience with big data technologies such as Hadoop, Spark, or Kafka.
Knowledge of containerization and orchestration technologies like Docker and Kubernetes.
Familiarity with DevOps practices and CI/CD pipelines.
Certifications in relevant technologies or frameworks (e.g., AWS Certified Big Data Specialty, Azure AI Engineer, Google Cloud Professional Data Engineer).
**Note**: This job description is intended to provide a general overview of the requirements for the position and does not encompass all the duties and responsibilities. The role may evolve and additional tasks and responsibilities may be assigned based on the organizations needs.
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