Lead - Senior Data Engineer - Snowflake

About Keyrus

Keyrus is a global consulting and technology company focused on making data matter — truly matter — from a human perspective. Founded in 1996, Keyrus operates in 28+ countries across 5 continents, with more than 3,300 people worldwide. Our strength comes from combining deep expertise in Data & Analytics, AI, Digital, and Management Consulting with a strong understanding of business realities. Data is never the goal in itself. We use data to shape understanding, design meaningful experiences, and enable better, real-life decisions. At Keyrus, we also believe companies have a responsibility beyond performance. Through our Foundation and ESG initiatives, we actively contribute to sustainability, inclusion, and positive societal impact.

The Role

As a Senior Data Engineer, focused on Snowflake, 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.

Your Impact

• 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.

What Makes This Role Challenging

• 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.

What We’re Looking For

Must-haves

• 8+ 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 integrate the deployment pipeline using git based tools.
• Experience in building 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.

Nice-to-haves

• Familiarity with Databricks for data engineering, notebook workflows, or distributed processing.
• Experience handling CI/CD pipelines for data workloads (e.g., GitHub Actions, GitLab, Azure DevOps, or similar).
• Knowledge of governance practices, including PII handling, RBAC, RLS, and data cataloguing.
• Understanding of reverse ETL concepts and tools.
• Experience with Data Viz tools for analytics and dashboarding (e.g. Qlik, Power BI).
• Experience in consulting environments and mentoring.
• Ability to champion best practices and keep up with innovations and trends on the data landscape.

How Our Salary Ranges Work

At Keyrus, salary ranges reflect different levels of mastery and impact within the same role — not different job titles.

• Bottom of the range: You meet the core requirements and will need ramp-up time and support.
• Middle of the range: You are fully autonomous from Day 1 and deliver consistently.
• Top of the range: You are a reference for the role, mentor others, and raise the bar for the team.

Final offers are based on experience, autonomy, scope, and market context, and are discussed transparently during the process.

What We Offer at Keyrus UK

• Competitive holiday allowance.
• Private Medical & Dental Insurance (Bupa).
• Group Life Insurance.
• Gym & fitness discounts via Pluxee (Sodexo).
• On-site gym access at our London office.
• Access to lifestyle discounts (travel, retail, entertainment & more) via Pluxee (Sodexo).
• Auto-enrolment pension scheme with Aegon.
• Training & Development via KLX (Keyrus Learning Experience).
• Strong focus on career development and internal mobility.
• Electric & hybrid car scheme via Tusker.
• Annual discretionary bonus, based on individual and company performance.
• Referral bonus for introducing new colleagues.

Why Keyrus?

Joining Keyrus means joining:

• A market leader in Data Intelligence.
• A company where people, trust, and diversity are core values.
• An environment that values ownership, flexibility, and innovation.
• A place where different backgrounds and perspectives are not just welcomed — they are essential.

We believe diversity drives better thinking, stronger teams, and better outcomes. Everyone belongs at Keyrus.

Equal Opportunity Statement

We are committed to building an inclusive workplace and encourage applications from all backgrounds, regardless of race, ethnicity, gender identity, sexual orientation, age, disability, or any other protected characteristic.