Data Engineer

🕒 Julho 21

🤠 Texas – Remoto

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⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

🚰 Engenheiro de Dados

🦅 Patrocina Visto H1B

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👻 Score fantasma 55%

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🗣️🇺🇸🇬🇧 Inglês obrigatório

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Sedgwick

10.000+ funcionários

🏗️ Construção

💼 Consultoria

🏥 Saúde

Construction • Consulting • Healthcare

A Sedgwick é uma fornecedora global de soluções de tecnologia para riscos, benefícios e negócios integrados. Eles ajudam pessoas e organizações a gerenciar e mitigar riscos com soluções em administração de sinistros de acidentes, saúde, invalidez, compensação por desemprego e responsabilidade, entre outros. A Sedgwick oferece serviços como administração de sinistros, consultoria de construção, contabilidade forense e engenharia forense. Suas especialidades incluem restauração de propriedades, proteção de marcas e prevenção de perdas em vários setores, incluindo agricultura, construção e setores ambientais. A empresa enfatiza diversidade, equidade e inclusão (DEI) e práticas ambientais, sociais e de governança (ESG).

Descrição

• Design, build, and maintain resilient ETL/ELT pipelines ingesting data from on-premise systems, AWS services, and Azure platforms for Snowflake and downstream AI services • Develop and maintain feature stores and analytically optimized datasets for machine learning workflows • Engineer generative AI data pipelines, including extraction, transformation, chunking, and loading of structured and unstructured data into vector databases • Act as a Snowflake power user and technical lead, implementing data modeling, Snowpipe automation, and compute and storage optimization • Execute non-invasive data extraction strategies from legacy systems while preserving system stability • Design and manage cross-platform workflows using Airflow, AWS Step Functions, and Azure Data Factory • Partner with IT, database administration, infrastructure, and security teams to resolve connectivity and access challenges and secure production approval for integrations • Implement automated data quality, validation, and observability frameworks • Optimize storage, compute usage, and query performance across Snowflake, AWS, and Azure • Partner with MLOps, Data Science, and AI teams to translate experimental use cases into scalable, production-ready data solutions • Perform other duties as assigned

🎯 Requisitos

• Master’s degree in Computer Science, Data Engineering, or a related field from an accredited college or university preferred • Six (6) years of hands-on data engineering experience, with a track record of building production-grade pipelines for Data Science and AI in multi-cloud environments or equivalent combination of education and experience required • Expert-level proficiency in Snowflake architecture, including data sharing, performance tuning, and integration with external cloud AI services • Advanced, hands-on knowledge of AWS (S3, Glue, Lambda) and Azure (Data Factory, Synapse) data services • Mastery of Python, SQL, and PySpark • Deep experience with data orchestration and containerization (Docker) • Proven ability to interface with on-premise SQL, mainframe extracts, and flat files and transform them for modern cloud consumption • Strong understanding of machine learning data needs, including feature engineering • Strong understanding of generative AI, including vectorization and embedding pipelines • Ability to work in a team environment • Ability to meet or exceed Performance Competencies • Ability to handle work-related stress and multiple priorities simultaneously • Ability to meet deadlines • Travel as required

🏖️ Benefícios

• Work-life balance • Reasonable accommodations when applicable and appropriate • Equal opportunity employer • Drug-free workplace • Diverse, equitable, and inclusive workplace

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