Senior Data Engineer

Founded in 2016, Katalon is the leading provider of a modern, comprehensive quality management platform. Katalon Platform enables quality assurance, DevOps, and software teams of any size to deliver world-class customer experiences faster, easier, and more efficiently.Since its first launch, Katalon has experienced tremendous growth, serving more than 30,000 teams around the globe, many of which are in the Fortune Global 500, such as PwC, KPMG, Abbott, etc. Katalon is recognized as a top automation tool by prestigious review sites, such as G2, Gartner, Capterra, and IT Central Station.  We are seeking a highly skilled Senior Data Engineer to join our Data team, driving the design, development, and maintenance of robust data architectures that support both production and operational data needs across the company. This role plays a critical part in enabling data-driven decision-making by building scalable, efficient, and secure data pipelines and infrastructure on AWS cloud services. You will collaborate closely with Engineering Architects, Growth Data Analysts, Product Data Analysts, and Revenue Analysts to ensure our data systems align with business goals and deliver actionable insights. Responsibilities include: Lead the design and implementation of scalable, reliable data architectures supporting production and operational data workflows. Build, optimize, and maintain ETL/ELT pipelines for efficient data ingestion, transformation, and integration from diverse sources into centralized data warehouses and lakes. Leverage AWS services (e.g., Redshift, S3, Glue, Lambda, EMR) and big data platforms such as Kafka and Airflow to architect and manage cloud-based data infrastructure. Collaborate with cross-functional teams including Engineering, Product, Growth, and Revenue to understand data requirements and translate them into technical solutions. Identify and implement improvements in data processing, storage, and delivery to enhance system performance and scalability. Ensure data quality, security, and governance best practices are embedded in all data engineering processes. Promote knowledge sharing of data engineering best practices within the team. Proactively troubleshoot and resolve complex data infrastructure issues. Drive the adoption of best practices in data engineering, including automation, monitoring, and continuous integration/deployment pipelines. Work in an Agile environment, collaborating closely with product and engineering teams to deliver data solutions that support SaaS product features and business growth.