Data /Senior Data Engineer

Data Engineer Role As a Data Engineer, you will play an important role in the Data Infrastructure team, responsible for building and maintaining a scalable, robust, self-service analytics platform. • Maintain and improve the ingestion pipeline to reliably deliver billions of events daily within a defined SLA. • Support teams in building and optimizing complex data pipelines. • Work closely with other teams to identify pain points and problems around the data platform. • Develop new tools and frameworks to improve the data platform. • Collaborate closely with data scientists and data analysts to support their work in production. • Work on large-scale initiatives such as building an ML platform and streaming use cases. • Establish best practices and processes around software and data development. • 3+ years of experience in data engineering. • Experience working with an orchestration tool, e.g. Airflow. • Experience working with large datasets. • Experience building complex ETL pipelines. • Experience working with cloud providers such as GCP, AWS, or Azure. • Strong programming skills in Spark with Scala and Python. • Experience with CI/CD tools such as Jenkins and Git. • Strong understanding of software engineering practices and principles. • Excellent problem-solving and communication skills. • Self-motivated, proactive, and able to take ownership of problems and drive them to resolution. Hands-on experience building, scaling, and operating production-grade data platforms or data infrastructure, including reliability, observability, performance, and self-service capabilities. • Experience working with messaging systems such as Kafka. • Knowledge of Kubernetes. • Hands-on experience with a streaming platform. • Experience managing a data warehouse in BigQuery or Redshift. Senior Data Engineer: As a Senior Data Engineer, you will design and build scalable data pipelines and data infrastructure powering Smart SMS features, including SMS categorization, fraud detection, spam intelligence, and AI-driven capabilities. You will work closely with Data Scientists, Data Analysts, and Product teams to develop robust data platforms, enable feature engineering for ML models, and deliver reliable datasets supporting product insights and decision-making for over a million daily users. Maintain and improve ingestion pipelines to reliably deliver billions of events daily within defined SLAs. • Support teams in building and optimizing complex data pipelines. • Work closely with other teams to identify pain points and problems around the data platform. • Develop new tools and frameworks to improve the data platform. • Facilitate a company-wide, data-driven culture. • Collaborate with Data Scientists and Data Analysts to support production use cases. • Work on large-scale projects such as building an ML platform and streaming use cases. • Establish best practices and processes around software and data development. • Experience working with an orchestration tool, e.g. Airflow. • Experience working with large datasets. • Experience building complex ETL pipelines. • Experience working with cloud providers such as GCP. • Strong programming skills in Spark with Scala and Python. • Experience working with CI/CD tools such as Jenkins and Git. • Strong understanding of software engineering practices and principles. • Excellent problem-solving and communication skills. • Self-motivated, proactive, and able to take ownership of problems and solve them. • Experience working with messaging systems such as Kafka. • Knowledge of Kubernetes. • Hands-on experience with a streaming platform. • Experience managing a data warehouse in BigQuery or Redshift. • Experience working with messaging systems such as Kafka. • Knowledge of Kubernetes. • Hands-on experience with a streaming platform. • Experience managing a data warehouse in BigQuery or Redshift.