Data Engineer - Senior
At a glance
Senior Data Engineering role at SOFTSWISS. Warszawa · full-time.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build dependable, self-service data products with Spark, Kafka, Delta Lake and related big-data tools
- Keep data pipelines fast and reliable by improving their architecture and checking data quality
- Adapt data solutions as business needs and technical limits change
- Work with internal teams to understand their data needs and help them use data products
What you bring
- At least five years in software engineering, including development, deployment and integration work
- Strong ability in a high-level programming language such as Scala, Java or Python
- Experience building large-scale Spark and Delta Lake ETL pipelines for feature engineering
- You can source and model application API data, build streaming applications, and set up pipeline monitoring
- Upper-intermediate English and strong Russian skills
Who this fits
This senior engineering role suits someone who can design and improve data-platform solutions while working with internal teams. You’ll need strong English and Russian skills.
From the employer
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
Our Benefits:
Private health insurance
Sports benefits
Comprehensive Mental Health Program
Free English lessons (online)
Local language courses
Paid time off
Maternity leave support
Referral program rewards
Upskilling, internal workshops, and participation in professional conferences and corporate events
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