Senior Data Engineer (Scala)

Visa Hunt; United States; Remote; USD 152,000 - 220,000; Full time

Benefits offered by this job

Remote work with US-hours overlap

Job summary

Visa Hunt is seeking a Senior Scala / Data Engineer to own and optimize data-intensive, distributed systems in production. You will design end-to-end pipelines and services, working closely with product and engineering teams to deliver scalable, low-latency solutions.

You should bring strong Scala experience, knowledge of Spark and Kafka, and a track record building fault-tolerant architectures. This six-month remote contract requires overlap with US business hours, and offers direct impact on

Qualifications

• Experience leading data-intensive projects in production.
• Strong design and architectural thinking for distributed systems.
• Proven ability to own end-to-end data pipelines.

Responsibilities

• Build and optimize distributed data processing systems using Scala.
• Design high-throughput, low-latency data pipelines.
• Work with Spark, Kafka and other big data frameworks.
• Develop scalable backend services for data workloads.
• Ensure fault tolerance and observability for pipelines.

Skills

Ownership mindset

Independent working

Problem-solving

English communication

Tools

Scala

Spark

Kafka

JVM

AWS

GCP

Flink

Akka Streams

Job description

Build data-intensive systems that actually scale. Own distributed processing, not just services. Shape how large-scale data flows power products.

We’re looking for a Senior Scala / Data Engineer for one of our clients — a company operating in a data-heavy, distributed systems environment. This is a hands‑on role for someone with a strong Scala background who has built and optimized high‑performance data systems in production.

This role is for someone who takes full ownership of distributed data systems — from architecture to performance. You’ll work on complex, large‑scale data processing challenges where efficiency, scalability, and fault tolerance are critical.

Your responsibilities will include:

• Build and optimize distributed data processing systems using Scala;

• Design and implement high-throughput, low-latency data pipelines;

• Work with big data frameworks (e.g., Spark) and distributed architectures;

• Develop and maintain scalable backend services for data-intensive workloads;

• Optimize performance of data processing jobs and infrastructure;

• Ensure fault tolerance and resilience of distributed systems;

• Implement monitoring, logging, and observability for data pipelines;

• Collaborate with engineering teams to design scalable system architectures;

• Contribute to cross‑functional backend and data engineering efforts;

• Ensure high standards of code quality, performance, and reliability.

What we expect from you:

• Strong experience with Scala in production environments;

• Proven experience as a Senior Data Engineer or Backend Engineer in data‑heavy systems;

• Strong understanding of distributed systems and parallel processing;

• Experience with big data technologies (Spark, Kafka, etc.);

• Strong knowledge of JVM ecosystem and performance tuning;

• Experience building high‑load, scalable systems;

• Strong system design and architectural thinking;

• Ability to work independently and take ownership;

• Strong problem‑solving skills in complex, distributed environments;

• English level: B2+ (C1 preferred);

• Availability to work in EU timezone.

Nice to have:

• Experience with functional programming paradigms;

• Experience with cloud infrastructure (AWS / GCP);

• Experience with stream processing frameworks (Flink, Akka Streams);

• Background in low‑latency or real‑time systems;

• Experience in niche or hard‑to‑hire tech domains.

We offer:

• Six-month full‑time contract engagement;
• Remote work with overlap in US business hours;
• High-impact project with direct influence on production AI systems;
• Close collaboration with client’s product and engineering teams;
• Opportunity to build core infrastructure for real‑world AI applications — not prototypes.