Data Engineer

🕒 July 21

🤠 Texas – Remote

🤠 Texas – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 55%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Sedgwick

WebsiteLinkedInAll Job Openings

10,000+ employees

🏗️ Construction

💼 Consulting

🏥 Healthcare

Construction • Consulting • Healthcare

Sedgwick is a global provider of technology-enabled risk, benefits, and integrated business solutions. They help people and organizations by managing and mitigating risk with solutions in accident, health, disability, unemployment compensation, and liability claims administration, among others. Sedgwick offers services such as claims administration, building consulting, forensic accounting, and forensic engineering. Their specialties include property restoration, brand protection, and loss prevention across several industries, including agriculture, construction, and environmental sectors. The company emphasizes diversity, equity, and inclusion (DEI) as well as environmental, social, and governance (ESG) practices.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

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

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