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Data Engineer (Snowflake)

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SeniorHybryda·Stockholm Metropolitan AreaFull-time

#460766·Dodano 8 dni temu·0

Źródło: justjoin.it

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Tech Stack / Keywords

Data modelingSecuritySQL PythonArtificial Intelligence (AI)strategyCI/CDTestingrisk analysisFinancial Services

Podsumowanie oferty

Lead Snowflake architecture for a multi-year data platform program at a major bank, delivering trusted datasets for business decisions, risk analysis, and regulatory reporting. Guide a migration from Snowpark (Scala) to dbt and Python, while keeping the production platform performant, secure, and cost-effective.

Wymagania

Profile & Qualifications:

Expert-level Snowflake architecture experience, including hands-on work in large, regulated data environments.
Proven experience architecting data platforms at scale, including organizing environments, schemas, and workloads for scalability and maintainability.
Strong software engineering fundamentals in Scala or Python, including object-oriented concepts and the ability to read, review, and reason about Snowpark (Scala) code.
Deep SQL and data modeling expertise at scale, including dimensional modeling and partitioning and incremental load strategies.
Ability to anchor architecture discussions, explain trade-offs, and make decisions.

Must Have:

Expert-level Snowflake knowledge, including micro-partitions, clustering, query optimization, virtual warehouse sizing, multi-cluster scaling, and caching.
Snowflake security architecture experience, including RBAC, secure views, masking policies, and data sharing.
Advanced SQL.
Solid fundamentals in Scala or Python.
Data modeling at scale.

Nice to have:

Snowpark (Scala or Python).
dbt.
Snowflake SnowPro Advanced: Architect or Data Engineer certification.
CI/CD tooling and data-quality or testing frameworks.
Airflow.
GitHub Copilot or similar AI coding assistants.
Experience in financial services or banking domains.

Obowiązki

Core Responsibilities:

Act as the team's authority on Snowflake architecture, including warehouse strategy, multi-cluster scaling, clustering keys, micro-partition pruning, query profiling, and performance diagnostics.
Define Snowflake project structure and migration standards, including database, schema, and warehouse layout, environment separation, naming conventions, and patterns for approximately 300 transformation jobs.
Own security and access architecture, including RBAC role hierarchy, secure views, data masking policies, and data-sharing design.
Review migration designs from a Snowflake perspective, including materialization strategy, incremental load patterns, and warehouse usage per workload.
Assess existing Snowpark/Scala transformation code to identify what can migrate cleanly and what may perform poorly when rebuilt.
Drive cost governance and compute efficiency through resource monitors, warehouse right-sizing, and identification of poorly tuned workloads.
Mentor engineers on Snowflake internals and performance reasoning.

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