Shape the future of data infrastructure by leading the design and operation of modern, cloud-native data platforms on AWS. In this role, you’ll take ownership of the full data lifecycle—from raw ingestion through curated analytics—delivering reliable, high-performance solutions for enterprise clients in a fully remote environment.
What You’ll Do
- Design and maintain scalable ETL/ELT workflows using AWS-native services, with deep integration across S3, Redshift Serverless, and Airflow
- Lead orchestration efforts in Apache Airflow, managing scheduling, dependencies, error handling, and alerting for production pipelines
- Build modular, well-documented data models in dbt using warehouse-first principles, ensuring analytics-ready datasets are consistent and reusable
- Implement robust data quality checks, testing frameworks, and observability practices across all pipeline stages
- Write clean, efficient Python code for data transformation, automation, and pipeline logic
- Collaborate directly with client stakeholders to understand requirements, present technical options, and guide decision-making
- Support the evolution of the data platform, including evaluation and potential adoption of Snowflake as a future data warehouse
- Participate in architectural reviews, retrospectives, and continuous improvement initiatives to strengthen platform reliability and team practices
What We’re Looking For
- At least 5 years of hands-on experience in data engineering or analytics engineering roles
- Proven track record working with AWS data services, especially S3, Redshift, and managed workflows
- Strong experience with Airflow for pipeline orchestration and operational support
- Proficiency in dbt, including modular modeling, testing, and documentation patterns
- Deep understanding of dimensional modeling, incremental load strategies, and data warehouse optimization
- Fluency in Python for scripting and pipeline development
- Excellent communication skills, with the ability to translate technical concepts for non-technical audiences
- Experience working independently in remote, distributed teams with client-facing responsibilities
Nice to Have
- Hands-on experience migrating to or implementing Snowflake
- Familiarity with pipeline monitoring tools such as Datadog, CloudWatch, Monte Carlo, or OpenLineage
- Background in data quality frameworks like dbt tests or Great Expectations
- Exposure to event streaming platforms such as Kinesis or Kafka
- Industry experience in fintech, lending, or financial services
- Experience guiding organizations through the shift from traditional data warehousing to modern analytics engineering practices
Environment & Culture
This is a fully remote role with a distributed team. You’ll work in a remote-first setting that emphasizes continuous learning, internal knowledge exchange, and participation in sponsored technical events across the AWS and data ecosystems. The role offers direct engagement with clients and the chance to influence high-impact data platforms at leading organizations across South Africa and beyond.
