Senior Data Engineer

We are seeking a highly skilled Senior Data Engineer to architect, build, secure, and optimize end-to-end data pipelines and enterprise-grade data platforms. The ideal candidate brings deep expertise in Python, Snowflake, modern cloud ecosystems, data warehousing design, and DevSecOps-led automation.

You will mentor junior engineers, drive technical decision-making, and lead solutions that improve data quality, performance, and reliability across the organization.

Responsibilities

Design and optimize scalable ELT/ETL pipelines using Python and SQL.; Build real-time, near-real-time, and batch data frameworks.; Implement CDC, SCD, incremental loads, schema evolution, and orchestration best practices.; Manage Snowflake environments including warehouses, databases, schemas, RBAC, and resource monitors.; Develop event-driven workflows using Snowflake Tasks, Streams, and Snowpipe.; Optimize performance and cost through clustering, caching, micro-partitioning, and warehouse sizing.; Build and maintain cloud-native data solutions using Azure Blob Storage, ADLS, Functions, ADF, and Purview.; Design Data Warehouses, Data Marts, and Semantic Layers.; Implement Kimball, Data Vault, and modern ELT design patterns.; Collaborate with BI and ML teams to operationalize analytics solutions.; Implement CI/CD pipelines using GitHub Actions, Azure DevOps, or GitLab CI.; Enforce DevSecOps practices including secret scanning, dependency scanning, IaC security, and policy-as-code.; Build and manage infrastructure using Terraform, Azure Bicep, or CloudFormation.; Implement data testing, schema validation, and contract enforcement.; Leverage pytest, Great Expectations, dbt tests, and automated profiling.; Develop data quality dashboards, lineage tracking, and SLA monitoring.; Lead design reviews, code reviews, and platform roadmap discussions.; Mentor engineers and drive engineering best practices.; Partner with Product, Data Science, and Business teams to deliver data-driven solutions.

Requirements

7+ 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.

Benefits

Flexible working environment; Volunteer time off; LinkedIn Learning; Employee-Assistance-Program (EAP)