GoMining

Build and operate secure, reliable GCP infrastructure with Kubernetes and Terraform, automate application delivery through CI/CD, and maintain observability, performance, and disaster recovery. | Requires strong hands-on GCP, Kubernetes, and Terraform experience, along with Linux administration, networking, and Python or Bash automation. | We are looking for a Senior DevOps / Platform Engineer to develop and operate GoMining's cloud platform. The primary focus of this role is GCP and Kubernetes, infrastructure and application delivery automation, and the reliability and security of production services. You will maintain and improve our existing infrastructure, contribute to the development of the next generation of our platform, and help product teams ship changes safely and efficiently. Responsibilities Develop and operate infrastructure in GCP, including GKE, virtual machines, networking, load balancers, storage, and managed services. Manage Infrastructure as Code with Terraform: develop modules, manage state and dependencies, ensure reproducible changes, and identify configuration drift. Operate Kubernetes: upgrade clusters and platform components, configure autoscaling, workload placement, network policies, and resource allocation. Develop CI/CD and GitOps using GitLab CI and Flux / Argo CD, automating builds, checks, deployments, controlled releases, and rollbacks. Build observability across metrics, logs, distributed tracing, and actionable alerting. Define and improve SLIs/SLOstogether with engineering teams. Troubleshoot production incidents and performance issues, conduct root cause analysis, and eliminate recurring failure patterns. Implement least-privilege access, environment and service isolation, secure secrets management and rotation, and infrastructure audit controls. Maintain backup processes and regularly validate recovery of critical data and infrastructure according to agreed RPO/RTO. Help engineering teams prepare services for production, including health checks, resource configuration, telemetry, and deployment procedures. Optimize cloud infrastructure usage and costs while maintaining reliability requirements. Maintain infrastructure documentation, operational runbooks, and recovery procedures. Strong hands-on experience independently operating production infrastructure and Kubernetes, including upgrades, troubleshooting, and disaster recovery. Strong experience with GCP, including GKE, Compute Engine, VPC, IAM, and Cloud Storage; good understanding of Cloud SQL, Cloud Logging, and Cloud Monitoring. Hands-on experience with Terraform, including modules, remote state, locking, importing existing resources, and safely applying infrastructure changes through CI. Deep knowledge of Kubernetes and containerization: Deployments, StatefulSets, Services, Ingress, storage, requests/limits, probes, autoscaling, RBAC, and NetworkPolicy. Experience with Helm and Kustomize. Strong Linux administration skills, preferably Debian/Ubuntu: processes, systemd, filesystems, disks, and resource troubleshooting. Strong networking fundamentals: TCP/IP, DNS, HTTP(S), TLS, routing, NAT, load balancing, and firewalls. Ability to troubleshoot connectivity issues across applications, Kubernetes clusters, networks, and cloud services. Experience building CI/CD pipelines, preferably with GitLab CI, and strong understanding of Git and GitOps principles. Understanding of runner permissions, secrets protection, and production deployment controls. Automation skills with Bash and Python, including maintainable infrastructure scripts and API integrations. Experience with monitoring, logging, and alerting using tools such as Prometheus, Grafana, or Cloud Monitoring. Practical experience operating PostgreSQL and understanding Redis and RabbitMQ, including availability, connections, replication or clustering, backup, and recovery. Strong understanding of cloud security principles: least privilege, service accounts, Workload Identity, secrets management, network segmentation, and access auditing. Ability to independently deliver infrastructure changes to a validated production result, explain technical trade-offs, and collaborate effectively with Engineering and Security teams. Nice to Have Experience with Flux CD, Argo CD, Ansible, and HashiCorp Vault. Experience with OpenTelemetry and distributed tracing. Experience migrating infrastructure between clouds or Kubernetes clusters, including database migrations with limited downtime. Experience designing disaster recovery strategies and conducting recovery exercises. Cloud cost optimization and capacity planning experience. Experience with DigitalOcean, Hetzner, or AWS. Ability to read and troubleshoot JavaScript / TypeScript applications. Experience operating financial or payment services with strict requirements around access control, auditing, reliability, and data integrity. 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).

Design and maintain scalable cloud-based data platforms and reliable data pipelines with monitoring and best practices implementation. | 6+ years in data engineering with strong software engineering and Python skills, plus hands-on experience with Google Cloud Platform and data modeling. | 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. ResponsibilitiesData 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 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. 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).

Build and own consumer research program including market sizing, segmentation, and brand health tracking, translating findings into actionable brand strategy recommendations. | 5+ years experience in consumer insights, market research, or brand strategy with strong quantitative and qualitative research skills and ability to manage agencies and translate data into commercial recommendations. | As Consumer Research Manager, you are the consumer insights function for GoMining marketing. You report directly to the CMO and work in a pair with the Brand Director: you produce the evidence, together you produce the brand strategy. You will establish the baseline that brand OKRs are set against, and you will own the research programme from question to decision — including the agencies who execute it. Responsibilities Build and own the consumer research programme: market sizing, segmentation, consumer usage & attitudes, brand health tracking, brand lift and more. Establish the brand and category baseline: awareness, consideration, differentiation, trust and barriers — by market and segment. Run concept, proposition, messaging and creative testing for brand and GTM launches, before spending commits. Own audience segmentation and the personas the whole marketing function uses — and keep them alive rather than filed. Run qualitative work directly where speed matters: user interviews, focus groups, community listening. Own research vendor relationships and briefs (brand trackers and ad-hoc studies), including scope, cost and quality control. Combine attitudinal research with behavioural and performance data from shared analytics colleagues to explain why, not just what. Track the competitive and category landscape as a standing input, not an occasional deck. Turn findings into decisions: recommendations that name the trade-off, not reports that describe the market. Build the measurement framework that makes brand and marketing OKRs verifiable quarter over quarter. 5+ years in consumer insights, market research or brand strategy — client-side, agency-side or both. Hands-on experience running brand health trackers and U&A studies: you have written the questionnaire, not only read the report. Strong quantitative skills — sampling, significance, weighting — and genuine qualitative craft. Experience managing research agencies and briefing them well enough to get useful output. You translate data into a recommendation and defend it in a room with commercial leaders. Experience with multi-market research and the comparability problems it creates. Experience building an insights function from zero. Fluent English. Nice to Have Crypto, fintech or investment-product category experience. Familiarity with product analytics tools and working alongside data teams. 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).