Data Engineer – Senior

Softswiss; Georgia; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health insurance

Sports benefits

English lessons

Language courses

Paid time off

Maternity leave support

Referral program

Upskilling programs

Job summary

SOFTSWISS is seeking a senior data platform engineer to build enterprise-scale data infrastructure powering analytics across the company. You'll work with a modern data stack, design robust pipelines using Spark, Kafka, and Delta Lake, and collaborate with cross-functional teams to meet evolving data needs. Strong English and Russian are desired.

This is a hands-on, impact-driven role in Georgia, USA. You will optimize performance, ensure data quality, and influence platform architecture while

Qualifications

• 5+ years of software engineering experience with development, deployment, and integration.
• Proficiency in at least one high-level language (Scala, Java, Python).
• Experience with large data environments and ETL pipelines.

Responsibilities

• Build self-service data products using Spark, Kafka, Delta Lake and other big data tools.
• Ensure pipeline performance and data quality with scalable architecture.
• Refine data solutions as requirements evolve.
• Collaborate with teams to understand data needs and promote adoption of data products.

Skills

Software engineering

Programming (Python/Java/Scala)

Analytics & problem solving

Education

Masters/PhD in CS/Math/SE

Tools

Apache Spark

Kafka

Delta Lake

Prometheus/Grafana

Spark Streaming

Job description

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

Main Advantages

• Private health insurance
• Sports benefits
• 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

SOFTSWISS recruitment communication is conducted only through official company channels. We never ask candidates to make payments, purchase equipment, share financial details, or transfer money as part of the hiring process. If you receive a suspicious message using the SOFTSWISS name, please verify it via [e-mail]