Early Career - Data Engineer

About the job:

As a Data Engineer, you will play a key role in building and maintaining the data infrastructure and systems that power AI/ML, analytics, reporting, and data-driven decision-making across the organization. You will be part of a cross-functional team, gaining hands-on experience working with modern data tools and cloud technologies while transforming raw data into actionable insights through collaboration with engineers and business stakeholders.

In this role, you will also have the opportunity to architect and lead the deployment of large-scale data engineering solutions, pioneering AI-driven data processing frameworks that integrate transformer-based LLMs, deep learning models, and traditional machine learning algorithms.

Key Responsibilities:

• Develop and maintain scalable data pipelines and ETL/ELT workflows for ingesting, processing, and transforming large datasets from multiple sources
• Build and optimize data models, schemas, and databases to ensure efficient data storage, accessibility, and performance
• Perform data cleaning, validation, and quality checks to deliver accurate and reliable data for analytical use
• Work with SQL, Python, and modern data tools such as Spark to automate data flows and support data science initiatives
• Architect and implement large-scale data engineering solutions across hybrid cloud environments
• Build reusable libraries and automated pipelines while applying software engineering best practices such as CI/CD, testing and monitoring
• Collaborate with analysts, engineers, and business teams to understand data requirements and deliver solutions
• Monitor data infrastructure performance and troubleshoot issues as needed
• Maintain documentation for pipelines, data models, and transformation logic
• Forecast emerging data needs, define design standards and drive strategic upgrades to storage and processing infrastructure
• Stay updated on emerging data technologies and recommend improvements to data architecture

• PhD in Electrical Engineering, Computer Engineering, Computer Science or related field of study
• Cumulative 3.0/4.0 GPA, or higher
• 2 years of relevant professional experience

Preferred qualifications

• Proficiency in programming languages such as Python, Java, Scala, C/C++ and strong SQL skills for data manipulation and querying
• Understanding of ETL processes, database concepts, and experience with big data platforms (e.g., Spark), cloud services (AWS, Azure, or GCP)
• Experience with AI/ML frameworks (e.g., PyTorch) and large-scale data processing, including transformer-based LLMs and neural networks
• Knowledge of machine learning algorithms ranging from traditional ML to cutting-edge deep learning models
• Strong analytical and problem-solving abilities with experience tackling complex, multifaceted challenges
• Exposure to or proven experience in machine learning, deep learning concepts, NLP, computer vision, speech, and time series analysis
• Demonstrated ability to develop end-to-end data pipelines, AI-enabled data tools, or enterprise-scale data architecture solutions
• Publications or conference presentations in AI/ML or data engineering topics
• Proven teamwork and communication skills in multidisciplinary projects, including ability to present technical concepts to non-technical stakeholders
• Strong time management and project management skills that enable on-time delivery of high-impact projects
• Demonstrated ability to build strong, influential relationships and leadership in cross-functional team environment
• Ability to work effectively in a fast-paced and rapidly changing environment with strong initiative and adaptability
• Ability to take initiative, drive for results, and drive innovation