Senior Software Engineer – Transition into Data Engineering

🕒 April 14

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Allata

WebsiteLinkedInAll Job Openings

201 - 500 employees

🤝 B2B

B2B • Consulting • Technology

Allata is a global consulting firm that helps businesses achieve digital excellence by crafting unique customer experiences, identifying revenue-generating opportunities, and improving operational efficiencies. They offer a wide range of services including strategic services, technology and cloud solutions, data and insights, and artificial intelligence development. Allata's approach is experience-led, strategy-aligned, tech-enabled, and data-driven. They work across multiple industries such as automotive, financial services, health and life sciences, high tech, logistics and transportation, among others, to drive modernization, personalization, innovation, and efficiency. With a team of former IT leaders and consulting professionals, Allata guides clients through complex digital landscapes to deliver value-based outcomes and help organizations integrate digital strategies seamlessly into their overall business strategies.

📋 Description

• Design, build, and support modern data pipelines and data platform solutions • Work with structured and semi-structured data in scalable cloud-based environments • Collaborate with engineers, analysts, architects, and business stakeholders • Help ensure data is reliable, scalable, and ready for analytics and business consumption • Apply software engineering best practices to data-focused solutions • Contribute to projects that support reporting, analytics, and data-driven decision-making

🎯 Requirements

• Strong experience in software development, ideally in backend or full-stack environments with Python or another backend-oriented programming language • Good working knowledge of SQL • Exposure to cloud platforms or modern data ecosystems • Familiarity with APIs, integrations, or data-related workflows • Exposure to concepts such as ETL/ELT, orchestration, or large-scale data processing

🏖️ Benefits

• Paid time off • Flexible work arrangements • Professional development opportunities • Structured training for Data Engineering tools and practices