Live opening · Posted 5 days ago
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About the role
Description supplied by the original job listing.
Our Technology teams are working on our new validation platform. Our clients around the world rely on data and insights to innovate and grow.
As a Senior Engineer, you’ll be part of a team of smart, highly skilled technologists who are passionate about learning and supporting cutting-edge technologies such as Snowflake Tasks, Streams, Pipes (Snowpipe), External Tables, components: Azure: Blob Storage, ADLS, Functions, ADF, Purview
Roles and Responsibilities
Data Engineering & Pipelines
Design, develop, and optimize scalable ELT/ETL pipelines using Python and SQL.
Build real-time, near-real-time, and batch frameworks using cloud-native services.
Implement incremental loads, CDC, SCD, schema evolution, and orchestration best practices.
Snowflake Engineering
Architect and manage Snowflake environments: warehouses, databases, schemas, resource monitors, RBAC, zero-copy clones, clusters, micro partition.
Implement Snowflake Tasks, Streams, Pipes (Snowpipe), External Tables for event-driven data workflows.
Optimize compute cost and query performance using clustering, micro-partitioning, caching, and warehouse sizing.
Cloud Engineering - Azure
Build and maintain solutions using cloud-native compute/storage components:
Azure: Blob Storage, ADLS, Functions, ADF, Purview
Data Warehousing & Modeling
Design enterprise-grade Data Warehouses, Data Marts, and Semantic Layers.
Implement Kimball, Data Vault, and modern ELT-first design patterns.
Work closely with BI/ML teams to operationalize features and analytics models.
AI engineering
Design, develop, and deploy AI and Generative AI solutions aligned with business requirements.
DevSecOps & Platform Engineering
Implement CI/CD pipelines for data engineering code (GitHub Actions / Azure DevOps / GitLab CI).
Enforce DevSecOps practices:
secret scanning
IaC security gates
dependency scanning
policy-as-code (OPA/Conftest)
Build infrastructure using Terraform / Azure Bicep / CloudFormation.
Automated Testing & Data Quality
Implement data unit testing, schema validation, and contract enforcement:
pytest
Great Expectations/dbt tests
automated data profiling
Build automated quality dashboards, lineage, and SLA monitoring.
Leadership & Collaboration
Lead design reviews, code reviews, and data platform roadmap discussions.
Mentor junior engineers and enforce engineering excellence.
Partner with Product, Data Science, and Business teams to deliver data-driven solutions.
Employment type
Full-time
Work arrangement
No
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