Senior Data DevOps Engineer Krakow · Full-Time · Remote Data

Appliscale sp. z o.o; Kraków; Hybrid; PLN 180,000 - 260,000; Full time

Job summary

Appliscale sp. z o.o. seeks a senior data/platform engineer to design, build, and operate analytics data ingestion pipelines and Databricks delivery services. You will modernize legacy components and implement CI/CD flows with automated tests to enable safe platform changes.

You will design production AWS infrastructure with Terraform, improve data quality, and collaborate with cross-functional teams on rollout plans and implementation strategies. Strong communication is essential.

Qualifications

• 5+ years of commercial experience in software/ data/platform engineering or related field.
• Bachelor's or higher degree in CS, software engineering or related field.
• Proficiency in Java, Python, or Golang in a professional setting.
• Knowledge of Infrastructure as Code tools such as Terraform.
• Experience with CI/CD tooling like GitHub Actions, Jenkins, Docker.
• Experience with streaming and schema-driven systems (Kafka, Protobuf, JSON Schema, schema registries).
• Experience with Airflow and DBT (Data Build Tool).
• Experience with Databricks, Spark/PySpark in production.
• Strong communication and teamwork skills.

Responsibilities

• Design, build, and operate services and pipelines powering analytics data ingestion and delivery to Databricks.
• Modernize legacy components by migrating services and deployment workflows to modern Java and standards.
• Develop CI/CD flows and integration tests to enable safe platform changes.
• Design and maintain production AWS infrastructure using Terraform and IaC tooling.
• Improve data quality with schema validation, metadata capture, and lineage tracking.
• Collaborate with cross-functional teams on design docs, rollout plans, and implementation strategies.
• Monitor live systems, troubleshoot incidents, and provide on-call support for analytics services.
• Support performance, reliability, and cost optimization across ingestion and processing pipelines.

Skills

Java

Python

Golang

Terraform

CI/CD

GitHub Actions

Jenkins

Docker

Kafka

Protobuf

JSON Schema

Airflow

DBT

Databricks

Spark

PySpark

Datadog

PagerDuty

Education

Bachelor's or higher degree in Computer Science or related field

Tools

Databricks

Kafka

Protobuf tooling

JSON-to-Protobuf

Terraform

GitHub Actions

Jenkins

Docker

Airflow

DBT

Job description

Our client is one of the largest game studios known for their very successful MOBA and FPS franchises. You will be a member of the Data Operations team focused on modernizing the Analytics Platform and building the services, tooling, and infrastructure that support data ingestion, schema management, and reliable delivery of analytics data into Databricks.

As a core contributor, you will play a vital role in building dependable data solutions capable of processing petabytes of information. Your work will span backend services, schema and metadata tooling, cloud infrastructure, CI/CD, and production operations. You will help product teams and internal platform users adopt new data standards, migrate safely from legacy systems, and operate their services with improved reliability, observability, and efficiency.

You will bring your experience working with large-scale data systems and production infrastructure to help design and operate a modern data platform that is easier to evolve, safer to change, and better aligned with future data engineering needs.

Responsibilities

• Design, build, and operate services and pipelines that power analytics data ingestion, schema management, and delivery into Databricks
• Modernize legacy platform components by migrating services, libraries, and deployment workflows to modern Java and application standards
• Build automation, CI/CD flows, and scenario/integration test coverage to make platform changes safe and repeatable
• Design and maintain production infrastructure in AWS using Infrastructure as Code tooling such as Terraform
• Improve data quality through stronger schema validation, metadata capture, lineage tracking, and operational guardrails
• Build tooling and paved paths that help internal customers migrate to new ingestion and schema standards
• Collaborate with cross-functional teams to prepare design docs, rollout plans, and implementation strategies for platform changes
• Monitor live systems, investigate incidents, and be part of the on-call team that provides 3rd line support to live analytics services
• Support performance, reliability, and cost optimization across ingestion and processing flows

Required qualifications

• Minimum of 5 years commercial work experience in software engineering, data engineering, platform engineering, or a related field
• Bachelor's or higher degree in Computer Science, Software Engineering, or a related field
• Coding skills, with commercial experience in one of the following languages - Java, Python, Golang
• Knowledge in Infrastructure as Code tooling, e.g. Terraform
• Experience with CI/CD tooling, e.g. GitHub Actions, Jenkins, Docker
• Experience with streaming and schema-driven systems, e.g. Kafka, Protobuf, JSON Schema, or schema registries
• Commercial experience with Airflow and DBT (Data Build Tool)
• Commercial experience with Databricks
• Commercial experience with Spark/PySpark
• Effective communication and teamwork skills

Nice to have

• Experience migrating legacy services or frameworks to modern application stacks
• Experience with Databricks Delta Live Tables and Unity Catalog
• Experience with AWS, especially Kafka/MSK-based data flows, S3, IAM and VPC/networking.
• Experience with Buf, Protobuf tooling, or JSON-to-Protobuf migration work
• Familiarity with Golang for internal tooling or automation
• Experience with infrastructure monitoring and on-call practices using tools like Datadog and PagerDuty
• Experience working with cross-discipline organizations that build data products
• Experience in the gaming industry, particularly with online multiplayer games
• Proficient in large-scale data manipulation across various data types
• Demonstrated ability to troubleshoot and optimize complex ETL pipelines