Data Engineer – Senior

Overview: We invite you to join our Data Platform team — building the data infrastructure that powers analytics and insights for SOFTSWISS. We process enterprise-scale data and serve multiple internal teams across the company. In this role, you’ll have the opportunity to: Work with modern data stack and AI tools to build complex solutions Design solutions to technical challenges and influence platform architecture Research, develop and integrate new data processing tools and technologies Key responsibilities: Build business-critical, robust and self-service data products using Apache Spark, Kafka, Delta Lake and other big data technologies Ensure pipeline performance and data quality through scalable architecture and optimization Refine data solutions as business requirements and technical constraints evolve Collaborate with teams to understand data needs and support adoption of data products across the company Required Experience: 5+ years of software engineering experience with expertise in development, deployment, and integration Proficiency in at least one high-level programming language (Scala, Java, Python or equivalent) Experience in data environments, such as Data Lakes, Data Warehouses, Data Marts, Data transformation concepts and working with large data volumes Experience in building ETL pipelines to perform feature engineering on large-scale datasets using Apache Spark and Delta Lake Experience with sourcing and modelling data from application APIs Experience with building stream-processing applications using Spark-Streaming, Kafka Streams or others Experience designing and implementing monitoring, alerting, and observability solutions for data pipelines using Prometheus, Grafana, Alertmanager or others Strong analytical and problem-solving skills Upper-intermediate proficiency in English and strong command of Russian Nice to have: Experience with workflow orchestration tools such as Apache Airflow Experience with Kubernetes and containerization Familiarity with cloud platforms (AWS, GCP, Azure, OCI) Familiarity with CDC and Debezium Familiarity with Clickhouse Familiarity with data quality validation frameworks for data pipelines Familiarity with Data Lineage Familiarity with low-latency NoSQL datastores (such as HBase, Cassandra, MongoDB), Relational databases (such as MySQL, Postgres) and Search systems (such as ElasticSearch, Solr) Masters, PhD, or equivalent experience in Software Engineering, Mathematics or Computer Science