Data Engineer – Snowflake

Darum lohnt es sich

• Design, build, and maintain pipelines and workflows that enable customers to use their data • Transform raw data sources into clean, reliable, and scalable data streams • Build scalable pipelines ingesting, transforming, and delivering data from EHRs, claims, APIs, and CRM systems into analytics-ready Snowflake structures • Integrate pipeline development with version control and CI/CD for repeatable deployments, change tracking, and approval gates • Analyze query profiles, optimize queries, and debug Snowflake workloads • Manage warehouse sizing, scaling policies, and credit/cost considerations • Work directly with client architects and analysts to explain and implement technical tradeoffs • Teach counterparts how to support and expand project deliverables • Adapt to new and unfamiliar technical challenges • Manage multifaceted work streams, schedules, deadlines, and personal work product • Anticipate issues and escape effectively • Mentor and guide others Requirements • 3+ years of professional experience in data engineering or related roles • 2+ years of hands‑on Snowflake experience in a production environment • Strong Snowflake development experience, including query profile analysis, query optimization, and debugging • Experience with virtual warehouse sizing, scaling policies, and credit/cost management • Experience with COPY INTO, Snowpipe, external stages, and external tables • Knowledge of clustering keys, micro‑partition behavior, materialized views, Time Travel, and zero‑copy cloning • Knowledge of Snowflake roles, grants, and RBAC hierarchy design • Proficiency in Python or another programming/scripting language such as Scala or Java • Experience with dbt, Snowflake Streams and Tasks, Dynamic Tables, Snowpark (Python), Apache Airflow, Azure Data Factory, or another orchestration framework • Solid grounding in ETL/ELT principles, dimensional and data‑vault‑style modeling, and data warehousing concepts • Experience with at least one major cloud provider (AWS, Azure, or GCP), including storage and networking basics as they relate to Snowflake integrations • Suitable home office to operate from • No relocation required Core Competencies Demonstrates expertise in building and maintaining data pipelines, with a strong focus on Snowflake development, query optimization, and data transformation.

Proficient in managing cloud integrations and mentoring team members to enhance project deliverables.

Highest-signal resume keywords • Snowflake Development • Data Pipeline Engineering • ETL/ELT Principles • Python Programming • Cloud Provider Experience ATS Optimization Keywords Hard Skills • Data Engineering • Query Optimization • Snowflake Workloads Debugging • COPY INTO • Snowpipe • External Stages • Materialized Views • RBAC Hierarchy Design • Dimensional Modeling • Data Warehousing Concepts Soft Skills • Mentoring • Problem‑Solving • Effective Communication • Adaptability • Time Management Industry Keywords • EHRs • Claims • APIs • CRM Systems • Cloud Integrations Tools & Technologies • Dbt • Apache Airflow • Azure Data Factory • Snowflake Streams • Snowpark