Data Engineer

Job Purpose

As a Data Engineer at SAAL.ai, you will be responsible for designing, building, and operating scalable and resilient data platforms that enable high-impact analytics, insights, and decision-making. You will work closely with product, analytics, and engineering teams to prototype, deliver, and operate reliable data pipelines and big-data services in production environments.

Key Responsibilities

• Define, design, and develop services for large-scale data ingestion, storage, and management across relational databases, NoSQL systems, log files, and event streams.
• Design, build, and operate scalable batch and streaming data pipelines in production environments.
• Ensure data platforms meet performance, reliability, scalability, and low-latency requirements.
• Develop highly concurrent systems for processing structured and unstructured datasets.
• Design and implement workflows and pipelines using tools such as Apache NiFi, Kafka, Spark, Flink, and Airflow.
• Support both batch and real-time data processing use cases.
• Collaborate with internal product teams and third-party service providers on system integrations and platform enhancements.
• Participate in sprint planning, development, and delivery activities.
• Ensure solutions are deployable, observable, and operationally manageable in live production environments.

Educational Qualification

Bachelor’s degree in Computer Science, Software Engineering, or a related field is preferred.

Experience

Minimum 5 years of professional experience as a Data Engineer or Big Data Engineer.

Essential Skills

• Strong experience in designing and operating data pipelines using Apache NiFi, Kafka, Spark, Flink, and Airflow.
• Solid understanding of distributed data architectures, data modelling, OLAP design, and change data capture (CDC), including tools such as Debezium.
• Experience with large-scale storage and messaging platforms, including MinIO/S3 and Kafka.
• Proficient in batch and real-time data processing, with familiarity in data formats such as Avro, Parquet, and ORC.
• Strong scripting or programming skills.
• Experience working in Agile environments and using version control systems such as Git.
• Experience delivering enterprise-scale analytics and reporting platforms, strong understanding of infrastructure and container-based deployments, and the ability to advise on emerging data technologies and best practices.