Mission of the Role

STRADVISION's SW Toolchain Team (referred to as STT) is seeking a talented team member to be responsible for the construction of Data Pipelines.In the STT department, we are responsible for providing the necessary Tool Chain for internal development at STRADVISION. Additionally, we deliver this software to our customers to evaluate our solutions and provide additional functionalities to our proprietary solutions. This software is intended for external use by our clients.The Senior Backend Engineer in STT will be responsible for constructing the Data Pipeline that supports the collection, transformation, storage, management, and provision of data in the Data Loop for ML implementation, working closely with team members.Due to the nature of the Data Pipeline, effective communication with both internal and external customers is required. Therefore, not only technical knowledge for constructing the Data Pipeline, but also documentation and communication skills are necessary.The role involves improving the existing Data Loop, implementing additional features, and managing it, requiring a proactive attitude to acquire the latest technical knowledge related to Data Engineering in line with the rapidly changing trends. Please note that translations may vary depending on the specific terminology and context used in the target language.

Key Responsibilities

• Data Collection: Collaborating with the System Engineering team responsible for data collection and standardization, we establish and maintain a raw data lake using the collected data. We also design and maintain the infrastructure for data transfer.
• Data Transformation: We implement and maintain the data ETL process to generate training/evaluation data required for the ML development process.
  Data Storage: Due to the nature of STRADVISION's Vision Perception Solution, data occupies a significant amount of space. Therefore, we establish and maintain a hybrid data storage solution, comprising on-premises and cloud storage.
• Data Management: Data is grouped, used, added, and modified within specific groups. We ensure traceability for each data and create evolving data groups by implementing and maintaining a data management solution.
• Data Provision: Data needs to be easily and quickly provided to MLOps or other applications. We collaborate with relevant team members to build and maintain HW/SW pipelines for efficient data delivery.

Basic Qualifications

• Minimum of 5 years of relevant experience, including at least 3 years of experience in Data Engineering.
• Experience in building end-to-end Full Stack Data Pipelines.
• Strong understanding of professional Backend engineering skills.
• Knowledge of ML Dev. Process/SW Dev. Process.
• Excellent communication and documentation skills.
• Experience in SRE (Site Reliability Engineering), including SLA design, monitoring, and incident response process.

Preferred Qualifications

• Experience with big data tools: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with AWS cloud services: EC2, EMR, RDS, Redshift
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: TypeScript, Python

Application

• Required : Resume
• Optional : Cover Letter

Recruitment Process

Application Review - Tech Screening Test - Interview Stage– Reference Check - Offer
(Please be aware of that the recruitment processes & schedules may be changed depending on the job and/or other circumstances. For example, onsite Interview may be replaced by video interviews due to COVID-19.)

Others

• Any job post may be closed earlier at any time, if position is filled.
• In case, there is any false information shared before/during/after the entire recruitment process, we can stop our recruitment process and also withdraw our offer/hiring confirmation.
• Interview schedules and the results will be informed to the applicant via the e-mail address submitted at the application stage.