Senior Data Engineer

Job not on LinkedIn

🕒 July 31

🇺🇸 United States – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 13%

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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Egis

WebsiteLinkedInAll Job Openings

10,000+ employees

🏗️ Construction

💼 Consulting

Construction • Consulting • Sustainability

Egis is a leading global architecture, consulting, construction engineering, and operating firm. They collaborate with clients to build a more balanced, sustainable, and resilient world by focusing on transport, infrastructure, and the built environment. With a strong emphasis on sustainability and digital transformation, Egis provides services across the entire project lifecycle, from idea to operation, in over 100 countries worldwide.

📋 Description

• The Senior Data Engineer is responsible for designing, implementing, maintaining, and optimizing a cloud-based data architecture and data pipeline ecosystem. • The position supports advanced analytics, machine learning operations, fraud detection initiatives, and investigative activities by delivering scalable, secure, and sustainable Azure-based data solutions. • The Senior Data Engineer develops and maintains modern ELT/ETL pipelines, data models, source-controlled environments, and operational standards that enable efficient data ingestion, processing, storage, and access. • Design, implement, and maintain scalable Azure-based data architecture supporting audits, investigations, and fraud analytics. • Develop, optimize, and sustain ELT/ETL pipelines within Azure Synapse Analytics and Azure Machine Learning environments. • Migrate and integrate large-scale datasets into Azure Data Lake Storage (ADLS). • Establish source control, version management, and development standards across data engineering assets. • Implement pipeline monitoring, validation, logging, and error-handling frameworks. • Design and maintain data models, data dictionaries, entity relationship diagrams, and architectural documentation. • Optimize ingestion, transformation, storage, and retrieval performance across diverse data sources and formats. • Develop self-service data access capabilities for analysts and investigators. • Collaborate with Data Scientists to ensure infrastructure effectively supports machine learning and AI initiatives. • Author and maintain Standard Operating Procedures (SOPs) governing data pipeline development, deployment, and monitoring. • Evaluate emerging AI-enabled engineering tools and LLM-assisted automation capabilities. • Recommend and implement architectural improvements that increase efficiency, reliability, security, and cost effectiveness.

🎯 Requirements

• Bachelor's degree in Data Engineering, Computer Science, Data Science, Machine Learning, Mathematics, or related discipline; or 5 years of relevant applied experience. • Five or more years of experience maintaining SQL database environments and performing advanced SQL/T-SQL operations. • Five or more years of experience designing and maintaining cloud-based ELT/ETL solutions. • Three or more years of experience working with Azure Synapse Analytics and Azure Machine Learning. • Three or more years of experience developing data solutions using Python and Pandas. • Experience supporting modern data platforms and cloud-native analytics architectures. • Demonstrated expertise in data architecture design, pipeline optimization, and operational support.

🏖️ Benefits

• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Remote work options

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