Senior Analytics Engineer

The role

The Senior Analytics Engineer builds, runs and improves the analytics platform, including infrastructure, pipelines and core data models. The role focuses on scaling the platform as data volumes grow while managing costs and performance.

What you will do

• Build and maintain the platform's AWS infrastructure
• Manage infrastructure as code in Terraform
• Administer the ClickHouse Cloud warehouse
• Host and maintain self-hosted tools including Apache Superset and Apache Airflow
• Build and maintain ingestion pipelines using AWS Glue, Airbyte and AWS Lambda
• Develop and optimise Spark jobs
• Design and maintain Iceberg tables
• Build and maintain Airflow workflows
• Develop and maintain dbt staging and core models in ClickHouse
• Build and maintain CI/CD pipelines in GitHub Actions

Required qualifications

• A bachelor's degree in Computer Science, Software Engineering or a related field, or equivalent practical experience
• At least 7 years in data engineering, software engineering or platform engineering roles
• At least 3 years building and running distributed data processing (Spark or equivalent) in production
• A track record of taking responsibility for a production data platform
• Experience working with datasets in the hundreds of millions to billions of records
• Experience running data workloads within real budget constraints
• Experience managing the cloud infrastructure that data workloads run on
• Experience in small teams where engineers cover a broad scope and work with limited supervision
• Experience working with remote teams across multiple countries and time zones
• Strong Python, written to production standards, with testing and modular design
• Advanced SQL, including writing and optimising queries against analytical databases
• Spark (PySpark), including performance tuning for partitioning, shuffles and data skew

Nice to have

• Experience in the non-profit, international development or social sector
• Apache Iceberg, or another open table format such as Delta Lake or Hudi
• ClickHouse, or a comparable columnar warehouse such as Snowflake, BigQuery or Redshift
• Terraform specifically
• Apache Airflow specifically
• AWS Glue and Lake Formation
• Data modelling for analytics, including handling reference data that changes over time
• Managed Spark platforms such as Databricks
• Streaming technologies such as Kafka, Flink, Kinesis or Spark Structured Streaming
• Event, telemetry or IoT data, particularly from devices that sync intermittently

About the company

Imagine Worldwide is a nonprofit organization that provides an innovative education technology solution to address the global literacy and numeracy learning crisis. They partner with governments, organizations, and communities to provide child-directed, tablet-based learning.