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# Mid/Senior-level GoLang Data Engineer (EU)

- **Company:** Inca Digital, Inc.
- **Location:** Hamburg, Germany (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Continuous Integration, Data Deduplication, Extract Transform Load (ETL), Data Systems, Relational Databases, Distributed Systems, Amazon DynamoDB, PostgreSQL, Enterprise Messaging Systems, MongoDB, NoSQL, RabbitMQ, Raw Data, Redis, Blockchain, SQL Databases, Structured Text, Management of Software Versions, Datadog, Concurrency, Backend, Git, Kubernetes, Apache Kafka, Restful APIs, Amazon Simple Queue Service (SQS), Terraform, Grpc, Data Pipelines, Docker, Golang, Microservices
- **Published:** September 11, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=2489afe58d6b5aaf

## About the Role

* 3+ years of professional experience developing backend services with Golang
 * Good knowledge of Go fundamentals, including concurrency, testing, etc
 * Experience with REST APIs and/or gRPC
 * Experience working in AWS environments
 * Experience with messaging systems such as Kafka/RabbitMQ/SQS/etc
 * Experience with SQL databases such as PostgreSQL
 * Experience with NoSQL databases such as MongoDB/Redis/DynamoDB
 * Familiarity with microservices and distributed systems
 * Experience with Docker, Git, and CI/CD

Nice to Have

 * Experience with Terraform
 * Experience with Kubernetes
 * Familiarity with observability tooling and practices

## Description

* Design, build, and operate end-to-end batch and incremental ETL/ELT pipelines, turning raw data into production-grade APIs, dashboards, and automated alerts.
 * High-throughput data acquisition from diverse sources: relational databases, third-party and vendor APIs, flat files, blockchain nodes and indexers, and social and web text at scale.
 * Develop NLP pipelines working with unstructured and semi-structured text data - entity and claim extraction, classification, deduplication, and enrichment feeding downstream risk models.
 * Case management, report generation, and intelligence portal supporting data systems.
 * Partner with the Head of R&D, engineers, data scientists, and our investigations team to translate intelligence requirements into scalable client-facing products.
 * Contribute to technical design and architecture in a written, argued design process.
 * Support improving system data quality and system maintenance: versioning, validation, lineage, reconciliation, and freshness monitoring.