Lead Data Engineer
We are looking for a highly skilled Lead Data Engineer to architect, build, and scale our modern data platform. This role will be responsible for designing robust data models, building scalable ELT pipelines, optimising Snowflake performance, and establishing engineering best practices across the data team.
Roles and Responsibilities
Architecture & Data Platform Ownership
Design and implement scalable, high-performance data warehouse solutions using Snowflake.
Define and maintain enterprise-grade data modelling standards (dimensional modelling, star schema, slowly changing dimensions, etc.)
Lead the migration or modernization of legacy data systems (if applicable)
Define best practices for data architecture, testing, documentation, and deployment
Data Pipeline Development
Build and maintain scalable ELT pipelines using Python and SQL
Develop and manage transformation layers using DBT
Optimize large-scale data transformations and ensure cost efficiency in Snowflake
Implement data validation and automated testing within DBT
Performance & Optimization
Optimize Snowflake compute and storage usage
Improve query performance and warehouse efficiency
Implement partitioning, clustering, and performance tuning strategies
Monitor data pipeline health and troubleshoot failures
Leadership & Collaboration
Provide technical leadership to Data Engineers
Conduct code reviews and enforce coding standards
Mentor team members on SQL optimization, modelling, and pipeline design
Work closely with business stakeholders to translate requirements into technical solutions
Governance & Quality
Ensure data accuracy, integrity, and consistency
Define and implement data quality frameworks
Establish version control and CI/CD processes for data workflows
Maintain documentation for models, pipelines, and architecture
Requirements
Skill and Qualificationas
Bachelor’s degree in Computer Science, Information Technology, or a related field with 5+ years of IT experience.
4+ years of experience in Data Engineering
Deep hands-on expertise in Snowflake (architecture, optimization, security, RBAC)
Strong experience in DBT (models, macros, testing, incremental models)
Advanced SQL skills (complex joins, window functions, query optimization)
Strong proficiency in Python (data processing, automation, scripting)
Solid understanding of data modelling concepts (fact/dimension tables, SCD types, normalization vs denormalization)
Experience designing production-grade data pipelines
Preferred / Good to Have
Experience with orchestration tools (Airflow, Dagster, etc.)
Experience with cloud platforms (AWS / Azure / GCP)
CI/CD implementation for data workflows
Experience handling large-scale datasets (TB+ scale)
Exposure to data governance and compliance standards
Signs you may be a great fit
Impact: Play a pivotal role in shaping a rapidly growing venture studio.
Culture: Thrive in a collaborative, innovative environment that values creativity and ownership.
Growth: Access professional development opportunities and mentorship.
Benefits: Competitive salary, health/wellness packages, and flexible work options.