Senior Data Engineer (Python, SQL, Snowflake, Devops, Azure/ AWS, Co-pilot, Kubernetes, Docker)

ONLY FOR DIVERSITY (FEMALE) CANDIDATES!!!!
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.
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.
Implement Snowflake Tasks, Streams, Pipes (Snowpipe) for event-driven data workflows.
Optimize compute cost and query performance using clustering, micro-partitioning, caching, and warehouse sizing.
Cloud Engineering (AWS | Azure | GCP)
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.
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.
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.
Preferred / Good-to-Have 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.

Employment type
Full-time

Work arrangement
No