Data Engineer

About the Position
We are seeking a Mid-Level Data Engineer to join the Data & AI Infrastructure team at MCINEXT as a Tech Lead Assistant. In this role, you will work closely with our Technical Lead to design, deploy, and optimize scalable data infrastructure and end-to-end processing pipelines.

A primary focus of this position is leveraging Kubernetes to maximize compute and storage utilization, improve system performance, and optimize infrastructure costs. You will be instrumental in analyzing system architectures, managing distributed databases, and bridging the gap between data platform operations and downstream AI/Data Science teams. This position offers an opportunity to tackle large-scale data engineering challenges and contribute directly to architectural governance and efficiency across high-impact enterprise projects.

Responsibilities
- Assist the Tech Lead in architecting, developing, and maintaining scalable and resilient ETL/ELT pipelines and data streams.
- Deploy, orchestrate, and manage distributed data services and workloads on Kubernetes, focusing on resource utilization, high availability, and cost efficiency.
- Analyze, benchmark, and fine-tune database performance across both relational (SQL) and non-relational (NoSQL) database engines.
- Design data models, unify heterogeneous data sources, and implement data governance to ensure quality, reliability, and integrity.
- Monitor system performance, uptime, latency, and infrastructure costs, actively driving optimization initiatives.
- Collaborate closely with AI, Machine Learning, and Software Engineering squads to deliver robust, low-latency data access and compute pipelines.
- Conduct R&D on emerging data engineering tools and paradigms, document technical architectures, and share knowledge across engineering teams.

Requirements
- 3 to 5 years of hands-on experience in Data Engineering and distributed data platforms.
- Proven experience deploying and maintaining containerized data workloads using Kubernetes, Docker, and Helm.
- Strong proficiency in SQL and solid programming experience with Python (Scala or Java is a plus).
- Deep hands-on experience with relational and NoSQL databases (such as PostgreSQL, MongoDB, or document/key-value stores).
- Working familiarity with workflow orchestration engines (e.g., Apache Airflow) and event streaming platforms (e.g., Apache Kafka).
- Solid grasp of distributed system design, data warehousing paradigms, and infrastructure efficiency tuning.
- Demonstrated experience working in production-level projects with cross-functional teams (5+ members).
- Exposure to cloud technologies, infrastructure as code (IaC), and modern CI/CD delivery workflows.
- Strong problem-solving mindset, ownership, and effective communication skills to collaborate seamlessly with the Tech Lead and product teams.

What We Offer
At MCINEXT, you will take part in building robust, high-volume data platforms that power critical, enterprise-scale AI and digital solutions. You will have access to massive computing resources, distributed architectures, and cloud-native environments.

We provide an environment centered on technical growth, architectural challenges, and close mentorship from engineering leadership, giving you the runway to advance your expertise in data systems and infrastructure leadership.