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Data Engineer - Core Systems Jobs (On-site work)

2558 Job Offers

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Data Engineer
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United States , Omaha
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Barbaricum
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Technical Systems Engineer - SME
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United States , McLean
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Arcfield
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Lead Data Engineer
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India , Noida
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3Pillar Global
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Geoint Systems Engineer
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United States , Aberdeen Proving Grounds; Alexandria
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Reinventing Geospatial
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Senior Software Engineer - Data Infrastructure
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United States , San Francisco
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180000.00 - 270000.00 USD / Year
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Plaid
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Data Engineer
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Poland , Kraków
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MDPI
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Data Engineer
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India , Jaipur
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InfoObjects
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Systems Engineer, Vehicle
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United States , Garden Grove
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140000.00 - 160000.00 USD / Year
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Harbinger Motors
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Senior Data Engineer
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United States , San Jose
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140000.00 - 350000.00 USD / Year
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Figure
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Senior Data Engineer
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Poland , Krakow
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EnergyHub
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Data Engineer - II
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India , Pune
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Atica Global
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Senior Data Engineer
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India , Hyderabad
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Appen
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Data Engineer SME
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United States , Chantilly
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AnaVation
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Senior Data Engineer
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United States , Dallas
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Robert Half
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Director of Engineering, Data Path Development
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United States
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155500.00 - 376000.00 USD / Year
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Hewlett Packard Enterprise
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Lead Data Engineer
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India , Gurugram
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Circle K
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Python Data Engineer
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India , Pune
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Citi
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Senior Data Engineer
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India , Mumbai
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Cogoport
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Data Engineer
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United States , Miami
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Robert Half
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Director Systems Engineering
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United States , Round Lake
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184000.00 - 253000.00 USD / Year
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Baxter
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Explore Data Engineer - Core Systems jobs and discover a career at the intersection of data infrastructure and fundamental business operations. Data Engineers specializing in Core Systems are the architects and builders of the reliable, scalable data pipelines that serve as the central nervous system for an organization. Unlike roles focused solely on analytics or machine learning, these professionals ensure that mission-critical internal systems—such as ERP, CRM, supply chain, and financial platforms—have robust, integrated, and trustworthy data flows. Their work directly underpins daily business functions, reporting, and operational intelligence. In this pivotal role, typical responsibilities revolve around designing, constructing, and maintaining the data architecture that supports core enterprise applications. This involves developing and managing ETL (Extract, Transform, Load) or ELT processes to consolidate data from various transactional systems into centralized data warehouses or data lakes. A core systems data engineer ensures data quality, consistency, and availability for downstream consumption, enabling other teams to perform accurate analysis and reporting. They are also responsible for optimizing data storage and retrieval for performance, implementing data governance and security protocols, and building monitoring systems to guarantee pipeline health and data integrity. Collaboration is key, as they frequently work with software engineers, database administrators, and business analysts to understand data requirements and translate them into technical solutions. The typical skill set for these jobs is a blend of strong software engineering principles and deep data expertise. Proficiency in SQL is fundamental, alongside advanced programming skills in languages like Python, Java, or Scala. Experience with cloud data platforms (AWS, Azure, GCP) and their associated services (e.g., Redshift, BigQuery, Azure Data Factory, S3) is highly common. Knowledge of data pipeline orchestration tools like Apache Airflow, data warehousing concepts, and data modeling techniques (dimensional modeling, data vault) is essential. Furthermore, familiarity with version control (Git), infrastructure-as-code, and an understanding of the specific data domains within core business systems (finance, logistics, etc.) are significant assets. Soft skills include problem-solving, clear communication to bridge technical and business teams, and a meticulous attention to detail to safeguard critical operational data. For those seeking Data Engineer - Core Systems jobs, this career path offers the challenge of building foundational infrastructure with a direct, tangible impact on business efficiency and decision-making. It is ideal for systematic thinkers who enjoy creating order from complexity and ensuring that an organization's most vital data assets are managed with precision and reliability.

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