Data Engineer

As a Data Engineer , 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.

• Define, design, and develop services for large‑scale data ingestion, storage, and management across relational databases, No
  
  SQL 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.

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

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

• 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.