Job details:

• Full-time
• Remote with occasional (1-2 times a year) travel to UK or Latvia
• 2 interviews
• Start date: ASAP
• Duration: 6 months + Extensions possible
• Client: big media company in UK

Scope:

• Design, build, and maintain scalable, reliable data pipelines (batch and streaming).
• Develop and optimise data models, warehouses, and lakehouse architectures.
• Build and automate CI/CD pipelines for data workflows and deployments.
• Ensure data quality, integrity, lineage, and governance across environments.
• Implement proactive monitoring and alerting for pipelines and data infrastructure (CloudWatch, Grafana).
• Manage IaC for consistent, reliable data infrastructure.
• Troubleshoot and optimise pipeline and query performance across environments.
• Lead incident resolution and root cause analysis for data systems.
• Collaborate with analysts, data scientists, and engineering teams, ensuring security, scalability, and operational excellence to understand data requirements and translate them into technical solutions
• Document data architecture, lineage, and workflows

Requirements:

• 5+ years in data engineering, with solid DevOps/platform engineering exposure.
• Strong SQL and data modelling skills (dimensional, normalised, lakehouse).
• Proficient in Python; working knowledge of Scala, Java, or Go.
• Hands-on experience with data pipeline/orchestration tools (Airflow, DBT).
• Experience with distributed processing frameworks (Spark, Flink, or similar).
• Advanced AWS expertise (Glue, EMR, Redshift, Athena, S3, Lambda, Kinesis).
• CI/CD tools (GitHub Actions, GitLab CI, Jenkins, CircleCI).
• Infrastructure as Code (CDK, CloudFormation). 
• Experience with streaming/event-driven architecture (Kafka, Kinesis, Apache Flink, or Pub/Sub).
• Fluent English

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