Solution Architect Principal Consultant

SOLUTION ARCHITECT - PRINCIPAL CONSULTANT

Cape Town, South Africa

About Datalab : At Datalab, our purpose is to empower businesses to unlock measurable value through data-driven insights and intelligent analytics.

We expertly design and implement end-to-end modern data solutions, with Snowflake at the core, complemented by carefully selected data technologies to ensure efficient, cost-effective, and future‑ready data ecosystems.

By combining innovation and deep expertise, we enable real‑time, actionable insights that help organizations become smarter, more agile, and more resilient in an ever‑changing digital landscape.

Why join Datalab

Flexible Work Arrangements : Enjoy hybrid work environment to suit your lifestyle.

Broad Technology Exposure : We offer experience across various data, analytics, and cloud technologies—so you'll always be learning something new about the modern data stack.

Career Growth & Development : We invest in our people through training, certifications, and mentorship, ensuring continual professional and personal advancement.

Opportunities to contribute to transformative, high‑impact data initiatives, grow your skills and be exposed to market leadership.

Collaborate with a dynamic, innovative team with a start‑up mindset that values autonomy, results, and professional growth.

Become a leading voice in data‑driven decision‑making, shaping how top‑tier enterprises operate and innovate.

About the Role

As a Data Architect Principal Consultant, you will design and deliver modern cloud data platform solutions with Snowflake as the centerpiece.

You’ll lead end‑to‑end implementations – from initial architecture and data modeling through pipeline development, deployment, and user enablement – turning complex data challenges into tangible business outcomes.

This is a leadership‑level role that demands both strategic vision and hands‑on technical skills to deliver scalable, innovative solutions for our clients.

Expect to remain deeply involved in technical delivery : working directly with Snowflake (leveraging its advanced capabilities), writing and reviewing code (SQL, Python), and utilizing modern data tools like Matillion and dbt for ETL / ELT, as well as analytics platforms such as Power BI, ThoughtSpot, and Sigma to drive end‑to‑end solution.

While you will engage in technical sessions with clients (e.g. requirements workshops, architecture reviews), your primary focus is on building and implementing high‑quality data solutions that deliver measurable value.

Key Responsibilities

• Architect Snowflake‑Centric Solutions – Lead technical discovery to understand business requirements and translate them into scalable data architecture and models centered on Snowflake.
• Data Modeling & Design – Develop and refine robust data models (e.g. dimensional schemas like star and snowflake) that optimize data organization for analytics and reporting.
• Design end‑to‑end data warehouse and lakehouse solutions on cloud platforms (AWS, Azure, or GCP) with Snowflake at the core, applying best practices for security and performance. This may include defining strategies to migrate legacy data systems to Snowflake and modernizing data architectures for the cloud.
• Build Data Pipelines – Implement and optimize data ingestion and transformation pipelines using modern ETL / ELT tools such as Openflow, Matillion and dbt.
• Integrate data from diverse sources (databases, APIs, streaming sources, third‑party platforms) into Snowflake, ensuring efficient, reliable data flow across the ecosystem.
• Leverage cloud‑native services and frameworks as needed to orchestrate workflows and automate data movement.
• Take a hands‑on role in developing data pipeline code (SQL, Python, etc.), conducting code reviews and design reviews to uphold best practices and quality standards.
• Implement testing, monitoring, and CI / CD automation in data pipelines to ensure reliability and repeatability of data processes.
• Proactively troubleshoot and resolve technical issues in data workflows to maintain smooth delivery.
• Governance & Security – Establish and enforce data governance policies, security controls, and compliance measures across Snowflake environments and data pipelines; manage access roles, data privacy compliance, and data cataloging in line with regulatory and client requirements.
• Performance & Cost Optimization – Continuously monitor and tune the performance of data stores and queries on Snowflake, optimizing clustering, indexing, and resource usage for maximum efficiency; recommend and implement strategies to balance performance with cost (e.g., sizing warehouses, pruning data, leveraging Snowflake features like caching and auto‑scaling) so that solutions remain cost‑effective and high‑performing at scale.
• Stakeholder Engagement – Work closely with client stakeholders (data engineers, analysts, product owners, and business leaders) to gather requirements and clarify objectives.
• Lead technical workshops and architecture review sessions to ensure alignment between business goals and the proposed data solutions.
• Clearly communicate complex data architecture concepts in an accessible manner to support client understanding and buy‑in.
• Serve as a trusted technical advisor during project delivery – presenting options and trade‑offs, guiding clients on best practices for data management (governance, security, cost optimization), and adjusting architectures based on feedback.
• Provide thought leadership by recommending appropriate tools or approaches (e.g. when to use particular integration tools or analytics platforms) to best meet client needs.
• Ensure high client satisfaction by aligning solutions with their strategic objectives and demonstrating tangible value.
• Lead Delivery Teams – Coordinate and lead the technical work of a delivery team (including data engineers, analytics engineers and customer success representatives) on client engagements.
• Provide direction and oversight through all project phases, conducting design and code reviews to ensure solutions adhere to Datalab’s standards and best practices.
• Foster an agile, results‑driven workflow, helping the team navigate challenges and achieve project milestones on time.
• Mentor junior analytics and data engineers by sharing expertise, best practices, and feedback to accelerate their professional growth.
• Contribute to Datalab’s internal knowledge base by developing reusable assets – such as accelerators, templates, and reference architectures – that improve our delivery capability and drive innovation.
• Encourage a culture of continuous learning and improvement within the team.

Qualifications & Experience

Must‑have :

Nice‑to‑have :

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