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