Senior Data Engineer, Keyrus

• 5+ years of experience in data engineering
• Proven experience in Snowflake (expert level: Snowpipe, Access History, Lifecycle Tags, Cortex AI, External Stages)
• Strong hands‑on experience with dbt (expert in modular modelling, documentation, testing)
• Ability to build ingestion pipelines using AWS S3, Fivetran, Snowpipe, and REST APIs
• Expertise in Cloud-based architecture (e.g. Azure, AWS)
• Strong analytical and problem‑solving skills, especially in handling JSON/VARIANT and schema‑on‑read patterns
• Advanced SQL skills (Jinja2 templating is a plus) and working experience with Python for API interactions
• Demonstrate strong ownership and work independently, taking responsibility for full-project delivery
• Ability to communicate clearly with both technical and non-technical stakeholders
• Fluency in English

Desirable

• As a Senior Data Engineer, you will work at the intersection of data, technology, and business, helping our clients turn complexity into clarity and insights into impact
• You will collaborate with multidisciplinary teams in an international environment and contribute to projects that drive performance, innovation, and sustainable growth
• Understand client needs and lead delivery end‑to‑end — proposing solutions that solve real business problems across ingestion, transformation, governance, and activation
• Build and manage scalable pipelines using Snowflake, Fivetran, Gong REST APIs, and Snowpipe
• Configure AWS S3 raw landing zones and Snowflake External Stages to ensure a durable, immutable raw data layer
• Deal with semi-structured data and expertly manage JSON/VARIANT payloads in Snowflake, implementing "schema-on-read" patterns to protect against upstream API changes
• Architect complex dbt models to parse, flatten, and normalise VARIANT data into structured tables
• Implement logic to merge issuer entities, contact records, and learner profiles across disparate systems to create a "Golden Record."
• Build semantic layers for predictive metrics, including Engagement Scores, Sentiment Trends, and Churn Risk
• Leverage Snowflake Cortex AI for predictive scoring and surfacing insights
• Maintain Governance and Security by implementing Role-Based Access Control (RBAC), PII masking (Dynamic Data Masking), and Row-Level Security (RLS) across the Snowflake environment
• Support clients in their data and digital transformation journeys
• You will work in complex, evolving client environments
• You are expected to balance delivery quality with pragmatism
• You will collaborate with diverse profiles across functions and cultures
• Autonomy increases with seniority — so does responsibility