Lead Data Solutions Architect

Description

Lead Data Solutions Architect

Summary of role:

Our Client is looking for a Data Solutions Architect to work within a dynamic, remote-first data architectural capability to deliver cloud-based data solutions using best-in-class RDBMS, ETL/ELT, and Cloud platforms for blue-chip customers across a range of sectors.

You will lead cross-functional teams of Data Engineers, Architects, Business Analysts and Quality Assurance Analysts to provision data processing, storage, and visualisation capabilities in an Agile environment. You will be comfortable with stakeholder engagement and take overall ownership of the technical delivery of your team and the solution they are building.

Experience and Leadership:

Proven experience in data architecture, with a recent role as a Lead Data Solutions Architect, or a similar senior position in the field.

Proven experience in leading architectural design and strategy for complex data solutions using Snowflake and then overseeing their delivery.

Experience in consulting roles, delivering custom data architecture solutions across various industries. Experience with Insurance is an added advantage. Architectural Expertise:

Strong expertise in designing, architecting and overseeing delivery of end-to-end data solutions (warehousing, pipelines, analytics) using Snowflake's Cloud Data Platform

Proficiency in conceptualising and applying Data Mesh and Data Fabric architectural patterns.

Experience in developing data product strategies, with a strong inclination towards a product-led approach in data solution architecture.

Extensive familiarity with cloud data architecture on platforms such as Snowflake, AWS, Azure and GCP. Integration of Snowflake with other cloud services (AWS, Azure, GCP) and big data tools.

Understanding of cloud platform infrastructure and its impact on data architecture. Data Technology Skills:

Deep hands-on experience with Snowflake's platform, features, and best practices with Strong understanding of data modeling principles and techniques

A solid understanding of big data technologies such as Apache Spark, and knowledge of Hadoop ecosystems.

Knowledge of programming languages such as Python, R, or Java is beneficial.

Knowledge of ETL/ ELT processes (such as DBT), SQL, NoSQL databases is added advantage.

Experience with data visualization tools and DevOps principles/tools is advantageous.

Familiarity with machine learning and AI concepts, particularly in how they integrate into data architectures. Design and Lifecycle Management:

Proven background in designing modern, scalable, and robust data architectures.

Comprehensive grasp of the data architecture lifecycle, from concept to deployment and consumption. Data Management and Governance:

Strong knowledge of data management principles and best practices, including data governance frameworks.

Experience with data security and compliance regulations (GDPR, CCPA, HIPAA, etc.). Leadership and Communication:

Exceptional leadership skills to manage and guide a team of architects and technical experts.

Excellent communication and interpersonal skills, with a proven ability to influence architectural decisions with clients and guide best practices. Project and Stakeholder Management:

Experience with agile methodologies (e.g. SAFe, Scrum, Kanban) in the context of architectural projects.

Ability to manage project budgets, timelines, and resources, maintaining focus on architectural deliverables. xjnqpsq Qualifications

Matric and a bachelor's degree in business administration, Information Systems, or related field.

SAFe or Scrum certified

Ad ID: 5417709419