Lead Data Engineer

Architect role for a hybrid work model requiring deep expertise in Fivetran, Data Build Tool and Snowflake for designing secure and scalable cloud data platforms. The architect will define standards, optimize data pipelines and mentor teams to deliver reliable analytics capabilities that drive informed decisions and measurable business outcomes for global stakeholders in a multinational environment., * Design robust cloud data architectures using Fivetran, Data Build Tool and Snowflake to deliver scalable and maintainable platforms that support complex analytics and reporting needs across business domains.

• Develop standardized patterns for data ingestion using Fivetran that ensure efficient extraction and loading from diverse source systems while maintaining consistency, reliability and clear operational observability. -Implement modular Data Build Tool models that transform raw datasets into curated, reusable and well documented data assets optimized for analytics performance and flexible self service consumption.
• Optimize Snowflake databases by defining appropriate clustering strategies, storage configurations and query patterns that balance cost efficiency, resilience and high performance for varied workloads.
• Establish comprehensive data modeling practices including naming conventions, layering strategies and documentation that promote clarity, reuse and long term sustainability of the data ecosystem.
• Coordinate with product teams, analysts and engineers to translate analytical and reporting requirements into end to end data solutions covering ingestion, transformation, storage and consumption layers.
• Define and implement data quality controls including validation rules, monitoring metrics and remediation workflows that improve trust in enterprise data and reduce downstream incidents.
• Drive automation of deployment pipelines for Fivetran, Data Build Tool and Snowflake configurations using version control and continuous integration practices to enable consistent and reliable releases.
• Partner with security and compliance stakeholders to embed robust access controls, encryption strategies and audit mechanisms within Snowflake and related components to protect sensitive information.
• Provide technical guidance to engineering teams by reviewing solution designs, troubleshooting complex issues and sharing best practices to uplift capability and ensure architectural alignment.
• Evaluate new platform capabilities, connectors and features in Fivetran, Data Build Tool and Snowflake, conducting structured experiments that validate value, performance and operational impact before adoption.
• Collaborate with operations and support teams to establish proactive monitoring, alerting and runbooks that reduce downtime, accelerate incident resolution and improve platform stability.
• Document reference architectures, design decisions and operational playbooks in clear and accessible formats that support onboarding, knowledge sharing and long term maintainability of the data landscape.

Primary skills - DBT, Snowflake. Optional - fivetran, Manufacturing domain experience. Must have lead data engineer at least 3 years and total the relevant 12 + to 16 years, * Possess a bachelors degree or equivalent experience in computer science information technology or a related field combined with at least twelve years of progressive work in data engineering or architecture.

• Demonstrate strong proficiency in designing and operating Fivetran based ingestion pipelines including experience with connectors scheduling configurations and error handling practices.
• Show advanced hands on experience with Data Build Tool including project structuring modeling tests documentation and integration with modern version control workflows.
• Bring deep practical knowledge of Snowflake features such as virtual warehouses time travel micro partitioning and query optimization for high volume and critical workloads.
• Apply solid understanding of data warehousing concepts star schemas data vault or similar modeling approaches and their application in large scale analytics platforms.
• Utilize proven experience with cloud platforms such as AWS Azure or GCP focusing on networking storage identity management and integration with Snowflake based solutions.
• Display familiarity with modern data observability tools logging practices and performance monitoring frameworks relevant to cloud data environments.
• Communicate complex architectural concepts clearly to technical and non technical audiences while influencing standards and encouraging adoption of best practices