Senior Software Engineer - Python with Snowflake

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.

6–10 years of professional experience in Data Engineering. Strong expertise in Python (pandas, asyncio, OOP, typing, packaging, pytest). Hands-on experience with Snowflake at enterprise scale. Advanced SQL skills—optimizing complex joins, window functions, CTEs, and performance tuning. Strong cloud background: AWS, Azure, or GCP. Deep understanding of data warehousing concepts: dimensional modeling, star schemas, data marts, CDC/SCD, modeling for high-volume pipelines CI/CD experience with GitHub Actions/Azure DevOps/GitLab CI. Experience with IaC tools like Terraform/Bicep. Strong understanding of DevSecOps practices: secrets management, IAM design, vulnerability scanning, zero trust principles Experience with orchestration tools (Airflow/ADF/Prefect/Step Functions). Excellent communication and stakeholder management skills. Experience with dbt (models, tests, exposures). Streaming platform experience (Kafka, Kinesis, Pub/Sub). Experience implementing OpenLineage, Marquez, or other lineage tools. Familiarity with Lakehouse architectures (Delta Lake, Iceberg, Hudi). Understanding of MLOps concepts and feature stores. Knowledge of cost governance and FinOps best practices. Prior leadership/mentorship experience.

Our Benefits Flexible working environment Volunteer time off LinkedIn Learning Employee-Assistance-Program (EAP) NIQ may utilize artificial intelligence (AI) tools at various stages of the recruitment process, including résumé screening, candidate assessments, interview scheduling, job matching, communication support, and certa