Data Operations Manager (Data Architect / Senior Data Engineer)

Job description

Project duration - 3 months+

Location - EU Only

Responsibilities

- Manage and optimise the Snowflake data warehouse, including query performance, warehouse sizing, resource utilisation, and cost efficiency.

- Maintain the reliability and performance of dbt projects, including data models, automated testing, documentation, and deployment processes.

- Oversee ELT pipelines, ensuring data availability, freshness, and compliance with established SLAs.

- Implement monitoring, alerting, and incident management processes, including root cause analysis and preventive measures.

- Establish data quality standards, automated validation, and observability practices across the data platform.

- Manage access controls, data governance policies, and compliance requirements.

- Monitor Snowflake consumption, implement cost optimisation strategies, and support platform budget planning.

- Develop operational runbooks, CI/CD workflows, and best practices for data engineering teams.

- Collaborate with Data Engineering, Analytics, BI, Security, and Finance teams to improve platform reliability and operational efficiency.

Requirements

- Extensive experience in Data Engineering, Analytics Engineering, DataOps, or Data Platform Operations.

- Strong hands-on experience with Snowflake administration, performance tuning, warehouse management, and SQL optimisation.

- Advanced proficiency in dbt Core or dbt Cloud, including incremental models, macros, testing, and deployment.

- Proven experience managing production ELT pipelines using Fivetran, Airbyte, Stitch, or similar solutions.

- Solid understanding of DataOps principles, CI/CD, version control, automated testing, and deployment pipelines.

- Experience implementing data quality frameworks, monitoring, alerting, and incident response processes.

- Understanding of data governance, access management, and data platform reliability.

Nice to Have

- Experience with data observability tools such as Monte Carlo, Elementary, or Datafold.

- Familiarity with workflow orchestration platforms such as Airflow, Dagster, or Prefect.

- Experience optimising cloud data platform costs, including Snowflake credit consumption and resource allocation.

- Knowledge of regulatory and compliance frameworks, including GDPR and SOC 2.