Senior Data Engineer / Analytics Engineer – AWS

This is a fully remote position, open to applicants in South Africa.

📋 Description

• Design, develop, and sustain efficient ETL/ELT pipelines within AWS-native data settings.

• Manage Airflow orchestration — including scheduling, dependencies, retries, alert notifications, and operational support.

• Create analytics-ready data models in dbt, utilizing modular, warehouse-first transformation methodologies.

• Operate confidently with S3 (raw, staged, curated) and Redshift Serverless for storage and warehousing.

• Contribute to the strategic roadmap and potential transition toward Snowflake as a future data warehouse.

• Write clean, maintainable Python code for pipeline logic, scripting, and lightweight engineering tasks.

• Integrate data quality, testing, and observability into every pipeline — ensuring it is a primary focus, not an afterthought.

• Implement sound version control, code review, and CI/CD practices for data workloads.

• Collaborate directly with client stakeholders: gather requirements, present solutions, and provide guidance on trade-offs.

• Partner with analysts, product teams, and fellow engineers in a distributed, remote-first environment.

• Participate in architectural reviews, retrospectives, and the continuous enhancement of platform practices.

⛳️ Requirements

• Over 5 years of experience in data engineering, analytics engineering, or related fields.

• Strong practical experience with AWS data platforms — focusing on S3-centered flows, cloud-native data workflows, and warehouse-driven delivery.

• Proven expertise with Apache Airflow — including design, maintenance, and troubleshooting of production pipelines.

• Proficient in dbt — with a solid grasp of analytics engineering patterns, modular models, testing, and documentation.

• Experience with data warehousing — Redshift preferred; Snowflake highly desirable; equivalent warehouse backgrounds will be considered if adaptable.

• Skilled in Python — capable of scripting for pipelines, transformations, and automation tasks.

• Strong understanding of data modeling techniques (dimensional, wide tables, incremental strategies).

• Excellent written and verbal communication skills — able to effectively convey technical concepts to non-technical audiences.

• Ability to work independently in a fully remote, client-facing setting.

🏝️ Benefits

• Culture of continuous learning.

• Internal knowledge sharing opportunities.

• Sponsorship for technical events.