Senior Data Platform Engineer: Scalable Pipelines & AI

Softswiss

Georgia

On-site

USD 120,000 - 180,000

Full time

2 days ago
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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

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

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