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Integration Developer / Data Engineer Jobs

4579 Job Offers

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Data Engineer
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United States , Wichita
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62500.00 - 95800.00 USD / Year
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Boeing
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Senior Data Engineer
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India , Vadodara
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MediaRadar, Inc.
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Senior Data Engineering Lead
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United States , Jersey City; Tampa
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176720.00 - 265080.00 USD / Year
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Citi
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Engineering Manager
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India , Hyderabad
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Amgen
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Data Scientist
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Pakistan , Lahore
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Not provided
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NorthBay
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Data Scientist
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Pakistan , Karachi
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NorthBay
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Data Scientist
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Pakistan , Islamabad
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NorthBay
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Graduate Data Analyst
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United Kingdom , Sheffield
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25000.00 GBP / Year
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GRAYCE
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Big Data Scala Engineer
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India , Pune
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Citi
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Project Engineer
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Belgium , Olen
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Belden, Inc
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Senior AI Product Manager
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United Kingdom , London
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Satalia
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Data Scientist - Computer Vision
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France , Paris; Bordeaux
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Mirakl
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Data Architect
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Bulgaria , Sofia
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HotSchedules Corporate
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Senior React Engineer
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Ukraine
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Honeycomb Software
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Forward Deployed Engineer (AI Agent)
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Canada
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Cresta
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Forward Deployed Engineer (AI Agent)
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United States
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150000.00 - 250000.00 USD / Year
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Cresta
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Senior Full Stack Engineer, Control Plane
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ACI Infotech
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Axway B2B Engineer-Service Support
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India , Noida
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Sopra Steria
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Software Engineer
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India , Bangalore
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Hewlett Packard Enterprise
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Engineering Manager – Order Management
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India , Bangalore
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IKEA
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Explore a world of opportunity in Integration Developer and Data Engineer jobs, a dynamic career path at the crucial intersection of data management and application connectivity. Professionals in this hybrid role are the architects of seamless data ecosystems, responsible for designing, building, and maintaining the pipelines that allow information to flow reliably between disparate systems. Their core mission is to break down data silos, ensuring that databases, cloud applications, CRM platforms, analytics tools, and legacy systems can communicate effectively, thereby unlocking actionable insights and powering business intelligence. Typically, an Integration Developer / Data Engineer engages in a full lifecycle of data integration. Common responsibilities include analyzing business requirements to design technical solutions, developing and optimizing Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) processes, and constructing robust data pipelines. They are tasked with ensuring data quality, consistency, and security throughout the integration flow. A significant part of the role involves ongoing monitoring, troubleshooting, and performance tuning of these pipelines to handle increasing data volumes and complexity. Collaboration is key, as these professionals regularly work alongside software developers, data analysts, business intelligence teams, and stakeholders to deliver cohesive data solutions that drive decision-making. The typical skill set for these jobs is a powerful blend of database expertise, cloud platform proficiency, and coding ability. Foundational knowledge includes strong SQL skills for complex querying and database manipulation, coupled with experience in at least one major programming language like Python, Scala, or Java. Familiarity with integration platforms and services is essential; this often encompasses cloud-based tools such as Azure Data Factory, AWS Glue, or Google Cloud Dataflow, as well as iPaaS (Integration Platform as a Service) solutions. Understanding data modeling, warehousing concepts (like star/snowflake schemas), and data governance principles is also highly valuable. As for requirements, employers generally seek candidates with a proven background in data engineering or software integration, a problem-solving mindset, and the ability to translate technical details into business impact. For those passionate about structuring the unstructured and creating order from data chaos, Integration Developer / Data Engineer jobs offer a challenging and rewarding career. This profession sits at the heart of digital transformation initiatives, making these professionals highly sought-after as organizations increasingly rely on integrated data to compete and innovate. Whether focusing on real-time data streams or batch processing, these experts build the critical infrastructure that turns raw data into a strategic enterprise asset.

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