About the role

Solutions Architect - Data Engineering

Job Summary:

We are on the hunt for a visionary Solutions Architect who thrives in dismantling conventions and pioneering innovative data solutions. This role is not just about problem-solving; it's about architecting the future of our data universe and enabling our AI ambitions through robust infrastructure that empowers our customers’ data intelligence ecosystems.

Key Responsibilities:

Architect: Design and build foundational data infrastructure that supports our enterprise-grade data platforms, owning the outcomes end-to-end.
Collaborate: Work closely with cross-functional teams including sales, engineering, and operations to ensure successful project delivery.
Master: Develop high-performance data ingestion pipelines while maintaining data quality and governance throughout the data lifecycle.
Implement: Utilize core GCP data services to design solutions that support advanced analytics and AI/ML initiatives.
Optimize: Continuously enhance data architectures for performance, efficiency, and cost-effectiveness within the cloud environment.
Translate: Convert complex business requirements into clear technical designs, providing guidance to data engineering teams.
Research: Stay ahead of technological trends by evaluating new data technologies and architectural patterns.

Requirements:

Experience: Minimum of 8 years in a Solutions Architect role focused on data engineering and platform building.
Cloud Expertise: Proven experience designing and implementing cloud-native data solutions, particularly with Google Cloud Platform (GCP).
Data Architecture: Thorough understanding of enterprise data architecture design with a focus on scalability and resilience.
Technical Skills: Proficiency in programming languages including Python and SQL for scripting and building data processing applications.
Data Ingestion & Orchestration: Hands-on experience with tools like Airflow and Kafka to manage data pipelines and workflows.
Advanced Data Modeling: Strong expertise in designing various data models for analytical and operational use cases.
Stakeholder Communication: Excellent ability to articulate complex technical concepts to diverse audiences.

Preferred Qualifications:

Databricks & BigQuery Mastery: Significant practical experience in utilizing Databricks as a core data warehouse and GCP BigQuery for analysis.
AI/ML Data Foundations: Experience in building data architectures specifically for Machine Learning and AI applications.
Cloud Data Strategy: Proven ability to strategize and implement effective cloud platform strategies in data environments.
Pre-Sales Expertise: Experience in crafting compelling technical narratives and proposals for clients.

Benefits:

Competitive Salary: Enjoy a salary package that reflects your skills and experience.
Flexible Working Hours: We offer a balanced work-life environment with flexible scheduling options.
Professional Development: Access to ongoing training and education opportunities to advance your career.
Health Benefits: Comprehensive healthcare coverage for you and your family.
Innovative Culture: Be a part of a collaborative and creative team that values your unique perspective and insights.
Remote Work: Opportunities to work remotely, allowing for a comfortable and productive workspace.
Inspiring Projects: Work on cutting-edge projects that push the boundaries of technology and innovation.