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About Our Client The organization operates in the technology sector, focusing on AI-driven products and research initiatives. It addresses the challenges of managing and processing large-scale datasets required for advanced artificial intelligence and machine learning applications. The company develops scalable data infrastructure and distributed data systems across cloud environments, enabling efficient data processing, experimentation, and model development for AI-focused projects. About the Opportunity The Data Engineer is responsible for developing and maintaining scalable data pipelines and infrastructure that support data processing, experimentation, and AI research. This role ensures reliable data architectures and workflows that enable teams to efficiently work with large datasets across distributed environments. The position collaborates closely with AI researchers, data scientists, and engineering teams to support data-intensive applications and advance the organization’s AI initiatives. Responsibilities • Design, build, and maintain scalable data pipelines to ingest, process, and transform large datasets from multiple sources • Develop and optimize distributed data processing workflows using Apache Spark and cloud-native technologies • Build and maintain scalable storage solutions across SQL and NoSQL database systems • Design and implement AWS-based data architectures supporting high-volume data ingestion and distribution • Develop efficient Python and SQL solutions for extracting, transforming, validating, and analyzing large datasets • Maintain high standards for data quality, integrity, monitoring, and operational reliability • Collaborate with AI researchers, data scientists, and engineering teams to support data-intensive applications • Implement automation, orchestration, and monitoring workflows for scalable data operations • Optimize data pipelines and infrastructure for performance, scalability, and reliability Requirements • Strong proficiency in Python, SQL, and distributed data processing frameworks such as Apache Spark • Hands-on experience with AWS data services and cloud-native data architectures • Experience working with both SQL and NoSQL databases • Experience managing and processing large-scale datasets in distributed environments • Strong understanding of data partitioning, performance optimization, and scalable data architectures • Exposure to AI/ML workflows or research environments is a plus • Experience with data visualization tools such as Matplotlib, Seaborn, or Plotly is beneficial • Familiarity with LLM-related data workflows is advantageous • Ability to work effectively in a remote-first environment and collaborate across technical teams Pay Range and Compensation Package • All employees are eligible for equity compensation • Performance-based bonuses may be available depending on the role and company policies • Comprehensive benefits package including health insurance reimbursement of up to 100% of premiums, paid time off, and a 401(k) plan with company match Benefits & Perks • Health insurance reimbursement of up to 100% of premiums • Paid time off • 401(k) plan with company match • Remote-first work environment Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin. Note: RemoteHunter is not the Employer of Record (EOR) for this role. Our purpose in this opportunity is to connect exceptional candidates with leading employers. We help job seekers worldwide discover roles that match their goals and guide them to complete their full application directly through the hiring company’s career page or ATS.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.