You will play a key role in designing and deploying the data infrastructure supporting Kolomolo’s modernization stack.
Your work will focus on building Terraform-based AWS deployments, ensuring smooth data ingestion, transformation, enrichment, and validation.
Responsibilities include: Designing and implementing Infrastructure as Code (IaC) using Terraform for AWS services.
Building data processing pipelines and automating workflows for ingestion, transformation, and validation.
Handling data enrichment and data integrity checks across multiple formats (e.g., Parquet, JSON, CSV).
Integrating data intake from relational databases (SQL, PostgreSQL, etc.) and graph-based data sources (e.g., Neo4j, Amazon Neptune).
Developing and maintaining Python-based data orchestration tools and scripts.
Working with containerized environments (Docker, Kubernetes) to enable scalable deployments.
Supporting continuous improvement and optimization of cloud infrastructure performance and cost.

Proven experience as a Data Engineer or Cloud Engineer in AWS environments.
Strong knowledge of Terraform and IaC practices.
Hands-on experience with AWS core services (S3, Lambda, Glue, ECS/EKS, Redshift, etc.).
Proficiency in Python for automation, scripting, and data workflows.
Understanding of ETL/ELT processes, data enrichment, and validation frameworks.
Experience working with containerization tools (Docker, Kubernetes).
Familiarity with multiple data formats, including Parquet.
Exposure to both relational and graph data models.
Good communication skills and experience collaborating in Agile/Scrum teams.
Experience with Databricks, Snowflake, or data lake architectures.
Knowledge of monitoring and observability tools (e.g., CloudWatch, Grafana, Prometheus).
Experience with CI/CD pipelines for data workflows.

Cloud Data Engineer – AWS, Terraform, Python

Key skills