Data Engineer

Job Purpose: As a Data Engineer, you will be responsible for designing, developing, and maintaining scalable data platforms and data pipelines that support analytics, AI, operational reporting, and data-driven products. You will work closely with software engineers, solution architects, data analysts, data scientists, and business stakeholders to build reliable, secure, and efficient data solutions. The role requires hands-on experience with modern data engineering technologies, batch and streaming data processing, cloud-native platforms, and distributed systems. The ideal candidate is passionate about data, enjoys solving complex engineering challenges, and is committed to delivering high-quality, production-ready data solutions.Job Description: Key ResponsibilitiesDefine, design, and develop data ingestion frameworks for large-scale data ingestion, storage, and management across structured, semi-structured, unstructured and streaming data sources.Design, develop, and maintain scalable batch and streaming data pipelines.Design and implement workflows and pipelines using tools such as Apache NiFi, Kafka, Spark, Flink, and Airflow.Design and implement data models supporting analytical and operational workloads.Collaborate with internal product teams and third-party service providers on system integrations and platform enhancements.Participate in sprint planning, development, and delivery activities.Deploy and support data workloads in cloud and containerized environments.Monitor, troubleshoot, and optimize data platform performance and reliability.Ensure solutions are scalable, observable, secure, and operationally manageable.Essential Skills & ExperienceStrong experience designing, building, and operating data pipelines in production environments.Experience working with modern Data Lake or Lakehouse architectures, including Delta Lake, Iceberg, or equivalent technologies.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.Experience integrating with enterprise systems through REST APIs, messaging platforms, and event-driven architectures.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 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.Familiarity with monitoring and observability tools such as Grafana, Prometheus, ELK/OpenSearch, Dynatrace, or equivalent.Experience working in Agile software development environments.Experience with Azure Databricks, Azure Data Lake Storage, Azure Event Hubs, and Azure Synapse Analytics.Understanding of data governance, data lineage, access controls, and data security best practices.Education and Qualifications: Bachelor's Degree in Computer Science, Software Engineering, Information Technology, Data Engineering, or a related discipline.Relevant professional certifications are advantageous.5–8 years of professional experience as a Data Engineer, Big Data Engineer, or Data Platform Engineer