Senior Data Engineer

GoMining; España; Híbrido; EUR 85.000 - 120.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Remote or hybrid format

Flexible hours across international 2n

Up to 20 vacation days + 8 holidays +

English learning support

Company retreats

Descripción de la vacante

GoMining is seeking a Senior Data Engineer with a strong software engineering background to design and build a modern cloud data platform. You will lead data infrastructure development, pipelines, and data contracts to enable analytics, ML, and product teams with high quality data.

Key responsibilities include shaping the data platform on Google Cloud (BigQuery, Dataflow, Pub/Sub, Composer), implementing IaC and CI/CD, and collaborating with Analytics, Data Science, and Engineering to improve

Formación

• 6+ years in Data Engineering with 3+ years in senior roles
• Strong software engineering with excellent Python skills
• Proven experience designing and building cloud-based data platforms and data warehouses
• Hands-on with Google Cloud Platform, including BigQuery, Dataflow, Pub/Sub, and Composer (Airflow)
• Experience building ETL/ELT pipelines, streaming architectures, and API integrations
• Experience with Terraform, Kubernetes, Docker, and CI/CD pipelines
• Strong understanding of data modeling, distributed systems, and scalable data architectures
• Experience implementing data quality, monitoring, and observability solutions
• Strong SQL skills

Responsabilidades

• Design, build, and evolve GoMining's cloud data platform on Google Cloud Platform
• Develop scalable data architectures following modern engineering principles, including Medallion Architecture
• Define and maintain data models, data contracts, and integration standards across systems
• Build and maintain reliable batch and streaming data pipelines
• Integrate data from internal services and third-party APIs
• Develop scalable ETL/ELT workflows and automate data processing
• Build and maintain analytical data marts for business and product teams
• Ensure data quality, consistency, and reliability across the platform
• Implement monitoring, alerting, and SLA management for data pipelines
• Continuously improve platform performance, scalability, and operational efficiency
• Drive Infrastructure as Code (IaC), CI/CD, and automation across the data platform
• Contribute to the development of ML and AI infrastructure
• Establish engineering best practices, code quality standards, and technical documentation
• Collaborate closely with Analytics, Data Science, Product, and Engineering teams

Conocimientos

Python

SQL

Herramientas

Google Cloud Platform

BigQuery

Dataflow

Pub/Sub

Composer

Apache Airflow

Terraform

Kubernetes

Docker

CI/CD

REST APIs

Git

Descripción del empleo

We are looking for a Senior Data Engineer with a strong software engineering background and deep expertise in building modern cloud-based data platforms.

You will be responsible for designing and developing scalable data infrastructure, building reliable data pipelines, and establishing engineering best practices across our data ecosystem. This role is ideal for someone who enjoys solving complex engineering challenges while enabling analytics, machine learning, and product teams with high-quality data.

Responsibilities

Data Platform

• Design, build, and evolve GoMining's cloud data platform on Google Cloud Platform
• Develop scalable data architecture following modern engineering principles, including Medallion Architecture
• Define and maintain data models, data contracts, and integration standards across systems

Data Engineering

• Build and maintain reliable batch and streaming data pipelines
• Integrate data from internal services and third-party APIs
• Develop scalable ETL/ELT workflows and automate data processing
• Build and maintain analytical data marts for business and product teams

Platform Reliability

• Ensure data quality, consistency, and reliability across the platform
• Implement monitoring, alerting, and SLA management for data pipelines
• Continuously improve platform performance, scalability, and operational efficiency

Engineering Excellence

• Drive Infrastructure as Code (IaC), CI/CD, and automation across the data platform
• Contribute to the development of ML and AI infrastructure
• Establish engineering best practices, code quality standards, and technical documentation
• Collaborate closely with Analytics, Data Science, Product, and Engineering teams

Technology Stack

• Python
• SQL
• Google Cloud Platform (BigQuery, Dataflow, Pub/Sub, Composer)
• Apache Airflow
• Terraform
• Kubernetes
• Docker
• CI/CD
• REST APIs
• Git

Requirements

• 6+ years of experience in Data Engineering, including 3+ years in Senior-level roles
• Strong software engineering background with excellent Python skills
• Proven experience designing and building cloud-based data platforms and data warehouses
• Strong hands‑on experience with Google Cloud Platform, including BigQuery, Dataflow, Pub/Sub, and Composer (Airflow)
• Experience building ETL/ELT pipelines, streaming architectures, and API integrations
• Experience with Terraform, Kubernetes, Docker, and CI/CD pipelines
• Strong understanding of data modeling, distributed systems, and scalable data architectures
• Experience implementing data quality, monitoring, and observability solutions
• Strong SQL skills

Nice to have

• Experience building ML infrastructure and supporting Data Science teams
• Experience with Kafka or other streaming platforms
• Experience working with fintech, crypto, Web3, or high-scale B2C products
• Experience with modern data lakehouse architectures
• Experience using AI tools to improve engineering productivity

Benefits

• Professional growth: support for courses, conferences, and English learning (up to 100% coverage)
• Work-life fit: remote or hybrid format with flexible hours across international teams
• Paid leave: up to 20 vacation days + 8 company holidays + 5 personal days per year
• Recognition programs: structured performance reviews and team awards
• Team culture: retreats in international locations (for example, company apartments in Cyprus)