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Ovoko \ RRR.LT
Ovoko \ RRR.LT
51 – 200 Darbinieki
Elektroniskā komercijaKonsultācijasLoģistika
Ovoko \ RRR.LT runs an online marketplace for used car parts, connecting auto dismantlers, recyclers, and other sellers with car dealers, mechanics, and automotive enthusiasts. Its catalog includes more than 23 million parts, with shipping across Europe and a 14-day money-back guarantee. The company also provides digital tools that help businesses manage inventory and sales in the automotive aftermarket, supporting the reuse of vehicle components through a circular-economy model.
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Vakances uzņēmumā

Senior Data Platform Engineer

Build the data infrastructure behind Ovoko’s used-car-parts marketplace, supporting analytics, AI, and product development. Work across Kubernetes, AWS, and Snowflake to keep data platforms reliable and scalable.

LTLietuvaHibrīdiPilna slodzeVecākais speciālistsNepieciešamā Valoda: angļuDatu inženieris
ApacheAWSGoGrafanaKafkaKubernetesMākonisPrometheusPythonTerraform

Apraksts

  • Build and scale Ovoko’s data platform for analytics, data science, AI, and product development.
  • Manage platform infrastructure spanning on-premises Kubernetes, AWS, and Snowflake.
  • Make architectural choices that support scalability, portability, maintainability, and adaptability.
  • Create self-service tools and CI/CD workflows for data code and infrastructure.
  • Support independent development and deployment of pipelines and dbt projects with separate environments, automated tests, and safe data publishing.
  • Run orchestration, streaming, query, and storage services, including upgrades, backups, recovery, and incident response.
  • Set up platform-wide observability with metrics, logs, alerts, and practical runbooks.
  • Manage access, secrets, security, and compliance according to least-privilege principles.
  • Plan capacity, tune performance, and optimize costs across Kubernetes, Snowflake, cloud infrastructure, and tools.
  • Provide secure, governed data access for AI assistants and agents, and infrastructure for commercial or self-hosted AI models.
  • Work with Data Engineers, Analytics Engineers, and the Infrastructure team.

Prasības

  • Hands-on experience in platform engineering, DevOps, or SRE, running production infrastructure for data platforms or backend systems.
  • Experience operating Kubernetes in production, including deployments, autoscaling, networking, and troubleshooting.
  • Practical experience with infrastructure as code such as Terraform and CI/CD pipelines such as GitHub Actions or GitLab CI; familiarity with GitOps.
  • Experience with cloud infrastructure, including networking, IAM, and cost management; AWS experience is preferred.
  • Experience configuring monitoring and alerts with tools such as Prometheus and Grafana, diagnosing performance issues, and handling production incidents.
  • Programming ability in Python or Go for automation and internal tools.
  • Understanding of data workloads and tools such as orchestration systems, data warehouses, streaming platforms, and dbt.
  • Practical knowledge of infrastructure security, including access controls, secrets management, and least-privilege principles.
  • Comfort using AI-assisted development tools in everyday engineering work.
  • Ability to work independently, make pragmatic technical trade-offs, and collaborate with Data Engineers, Analytics Engineers, and the Infrastructure team.
  • Preferred: Hands-on experience with Kafka and Apache Flink.
  • Preferred: Experience running Apache Iceberg in production.
  • Preferred: Experience designing and operating hybrid data platforms across on-premises and cloud environments, including incremental replication, CDC, and upsert patterns.

Priekšrocības

  • Private health insurance
  • Employee stock option plan (ESOP)
  • Budget for personal and professional learning
  • Commuting support, with covered parking or public transport
  • Snacks and drinks at work
  • Onsite gym
  • Choice of MacOS or Windows hardware and software
  • Option to work from anywhere for up to 30 days per year
  • Employee referral program

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