المسمى الوظيفي

About the Company

Our client, based in Auckland, is a prominent AI and Data Analytics consulting firm that has been enabling organizations in the ANZ region to achieve superior outcomes using data and technology for three decades. They have collaborated with major healthcare, life sciences, financial services, and government sectors throughout the region.

Role Overview

They are looking for a highly skilled Data Practice Lead to join a vibrant and innovative team, focused on driving impactful data strategies and solutions.

Key Responsibilities

Work closely with senior data stakeholders to enhance sales, recruitment, account management, consulting services, and practice operations.
Play an integral role in their expanding Databricks Center of Excellence, leading and delivering Databricks-focused projects.
Serve as a Databricks subject matter expert, assisting business development and advising clients on best practices in architecture, data engineering, and scalable analytics.
Champion innovation and team performance by fostering ownership, output-focused work, and employee wellness.
Oversee project risks including planning, budgeting, delivering on commitments, and aligning with executive leadership.
Expand the company's market presence by crafting proposals, scopes of work (SOWs), and account growth strategies.
Offer technical and architectural guidance on Databricks, modern data platforms, and cloud-native solutions to clients and staff.
Mentor team members and act as a thought leader by recommending cutting-edge technologies aligned with client objectives and future data strategies.
Approach every client interaction with a business-first perspective, driving technology-enabled results that enhance competitive advantage.

Technical Duties

Architect and deploy scalable data solutions using Databricks, utilizing platform features such as Delta Lake, Iceberg-based Uniform, Delta Live Tables, and Unity Catalog.
Lead and nurture engineering teams, promoting best practices in data management and optimizing system performance.
Collaborate with clients to understand challenges and design tailored solutions leveraging Databricks capabilities.
Provide hands-on leadership in building various layers of Data Lakehouse platforms to meet client-specific demands.

Candidate Requirements

At least 8 years of experience in data engineering or architecture, including 4+ years directly working with Databricks and its key products like Delta Lake and Unity Catalog.
Extensive knowledge of big data platforms and cloud data warehouses.
Strong understanding of Databricks architecture on major public clouds (AWS, Azure, GCP) with experience deploying scalable environments from the ground up.
Expertise in designing and implementing extensible data models (Silver and Gold layers) adhering to methodologies such as Star Schema and Data Vault.
Advanced skills in object-oriented programming languages including Java, Python, and PySpark, along with tuning and optimizing complex data pipelines.
Experience with container orchestration systems and AI/ML platforms.
Competence in streaming data ingestion and contemporary data workflow management.
Demonstrated history of delivering large-scale migration and modernization projects moving legacy data warehouses to Databricks Lakehouse platforms.
Familiarity with estimating Databricks consumption based on diverse Data & AI pipeline workloads across environments.
Experience with designing and implementing disaster recovery solutions for extensive Databricks platforms is highly desirable.
Preferably holds Databricks Data Engineering Professional certification and has managed multiple complex Databricks project implementations.

Databricks Architect