Solution Architect Principal Consultant

Datalab; Cape Town; Hybrid; ZAR 1 200 000 - 1 600 000; Full time

Job summary

A leading data consultancy in Cape Town is seeking a Principal Consultant who will design and deliver cloud data solutions using Snowflake. The role involves leading projects from architecture to deployment while engaging with clients and mentoring junior engineers. Candidates should have over 8 years in data engineering, including significant experience with Snowflake. This position offers a hybrid work environment and opportunities for professional growth.

Benefits

Flexible Work Arrangements

Broad Technology Exposure

Career Growth & Development

Qualifications

• 8+ years of experience in data architecture or engineering roles.
• 3+ years of experience designing Snowflake solutions in production.
• Ability to mentor junior engineers.

Responsibilities

• Design and deliver cloud data platform solutions with Snowflake.
• Lead end-to-end implementations from architecture to deployment.
• Engage with clients to gather requirements and deliver solutions.

Skills

Snowflake expertise

SQL proficiency

Python programming

Data modeling

ETL/ELT tools

Analytical skills

Cloud platforms knowledge

Communication skills

Education

Bachelor's or Master's degree in Computer Science, Data Engineering, or related field

Tools

Snowflake

Matillion

dbt

Power BI

Job description

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 :

• • Bachelor's or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field (or equivalent practical experience).
• 8+ years of experience in data architecture, data engineering, or related roles, with at least 3+ years designing and implementing solutions on Snowflake in production environments.
• Proven track record of delivering large‑scale data solutions (data warehouses, data lakes, or lakehouses) that align with business needs.
• Expertise in the Snowflake data platform, including knowledge of its advanced features and architecture best practices for performance tuning (e.g., clustering, query optimization), data sharing, zero‑copy cloning, time travel, and role‑based access control.
• Strong SQL skills (ability to write and optimize complex queries) and proficiency in a programming/scripting language such as Python for data processing and automation.
• Hands‑on experience with modern data integration tools and frameworks (e.g., Matillion, dbt or similar) for ETL / ELT, and familiarity with BI / analytics tools for data consumption (e.g., Power BI, ThoughtSpot, Sigma).
• Ability to design data pipelines and transformation workflows that feed analytics dashboards and reports effectively.
• Solid understanding of data modeling principles and methodologies – including designing dimensional models (star / snowflake schemas) and normalized models – and experience implementing enterprise data warehouses or data lakes.
• Capable of translating complex business data requirements into efficient schema designs and optimizing data structures for query performance.
• Strong understanding of cloud platforms (AWS, Azure, and / or GCP) and their native data services (e.g., storage, messaging, data integration services).
• Experience deploying or integrating Snowflake within a cloud ecosystem and optimizing for cloud infrastructure is required.
• Excellent communication and stakeholder management skills, with the ability to work directly with clients and cross‑functional teams.
• Demonstrated leadership in a technical capacity – for example, experience guiding a team of engineers or leading technical projects – and a willingness to mentor others.
• You should be comfortable presenting solutions to both technical and non‑technical audiences and collaborating in a consulting / client‑facing environment.

Nice‑to‑have :

• Snowflake SnowPro Advanced : Architect certification (or equivalent Snowflake advanced certification) strongly preferred, as it attests to your expert knowledge of Snowflake’s design and implementation best practices.
• Certifications in AWS (e.g., Cloud Practitioner).
• Prior experience in a consulting firm or in a client‑facing role where you led data‑focused projects is highly valued.
• Experience designing solutions for streaming data integration or working with data science teams (ML / AI initiatives) is a bonus that indicates versatility.