Data/ML Solution Architect

📋 Description

• Spearhead the design and execution of data and AI/ML architecture solutions across both cloud and on-premise environments.

• Manage intricate customer engagements, delivering strategic technical insights and ensuring solutions align with client business objectives.

• Forge and sustain robust relationships with key customer stakeholders, serving as a reliable technical advisor.

• Facilitate technical workshops, training sessions, and presentations.

• Define and implement data lifecycle processes: ingestion, storage, processing, and visualization.

• Collaborate with business units and stakeholders to ensure solutions meet business objectives.

• Guarantee compliance with security, architecture frameworks, and regulations (e.g., AWS Well-Architected, GCP Architecture Framework).

• Lead cross-functional teams, offering mentorship and guidance to technical talent.

• Design and implement proofs of concept for emerging technologies such as Generative AI and Machine Learning.

• Promote best practices for backend/ML services to achieve scalable and maintainable solutions.

• Supervise data governance and data quality processes across various platforms.

• Remain abreast of the latest technology trends and continually enhance the architecture strategy.

⛳️ Requirements

• Over 7 years of experience in solutions architecture, emphasizing Big Data and cloud platforms (AWS, GCP, Azure).

• Exceptional communication and problem-solving skills, capable of managing multiple projects while effectively conveying complex technical concepts to both technical and non-technical audiences.

• Experience in technical sales or pre-sales related to cloud, big data, and ML solutions.

• Strong leadership and team collaboration skills.

• Strategic mindset focused on delivering measurable business outcomes.

• Proven capacity to forge strong customer relationships and function as a trusted advisor.

• Expertise in data engineering and analytics, designing data pipelines and architectures using AWS, GCP, or Azure data stack.

• In-depth understanding of AI/ML concepts and experience in integrating AI/ML components into solutions.

• Demonstrated experience with data lakes, data warehouses, and real-time data analytics.

• Proven track record with microservice architecture and containerized deployment options.

• Practical experience with Kubernetes, Docker, and containerized applications.

• Proficient in backend-related programming languages such as TS, Java, Python, and others.

• Solid understanding of machine learning and MLOps tools (PyTorch, SageMaker, MLFlow).

• Demonstrated ability to lead and mentor cross-functional teams.

• Familiarity with agile methodologies.

• Nice to Have:

• Experience in implementing Generative AI.

• Proficiency with graph databases (Neo4j, AWS Neptune).

• Knowledge of data mesh principles and data contracts.

• Operational knowledge of infrastructure deployment tools such as AWS CDK, CloudFormation, and Terraform.

🏝️ Benefits

• Competitive salary and performance-based incentives.

• Comprehensive health and wellness benefits.

• Opportunities for professional development and career advancement.

• Flexible working arrangements and a supportive work environment.