We are seeking a Senior Data Engineer to join a high-performing global engineering team building a

next-generation data intelligence platform. This role is ideal for someone who enjoys solving non-

trivial engineering problems, proposing innovative solutions, and taking end-to-end ownership of

technical initiatives.

About the Product

You will work on data products that power complex data processing pipelines, transform and enrich

large-scale datasets, and support advanced data science workloads. The goal is to build a next-gen

SaaS solution enabling omni-channel insights for global enterprises.

Key Responsibilities

• Develop and enhance new product features with a strong focus on scalability and

performance.

• Modernize existing system components by redesigning them to align with new architecture

paradigms.

• Deeply understand the business domain, customer needs, and core use cases.

• Own and deliver complex engineering tasks end-to-end.

• Ensure adherence to non-functional requirements (stability, scalability, performance).

• Mentor junior engineers and influence technical decision-making.

• Work within a Scrum team and collaborate with cross-functional groups to solve challenging

technical problems.

Requirements

• Minimum 5 - 7 years of hands-on experience with Python/Spark/Airflow.

• Strong SQL skills with experience working on relational and NoSQL databases (Snowflake is

a plus).

• Strong understanding of data models, ETL/ELT pipelines, and batch/real-time processing.

• Practical experience in Scala or Java.

• Experience with Docker, Kubernetes, and containerized environments.

• Solid experience building solutions on cloud platforms.

• Strong understanding of DevOps methodologies.

• Experience working in an Agile/Scrum environment.

• Passion for modern data engineering technologies and continuous learning.

• Ability to quickly dive into development activities and deliver high-quality code.

• English proficiency: B2 or above.

Nice to Have

• Understanding of distributed system architecture and challenges.

• Experience with GCP stack (DataProc, Composer, GCS).

• Exposure to AI/ML, statistical tools, or related technologies.