Senior Data Engineer – Analytics Engineer, AWS

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🕒 April 20

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DVT

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 1999

🤝 B2B

☁️ SaaS

🤖 Artificial Intelligence

B2B • SaaS • Artificial Intelligence

DVT is a global custom software development and data engineering company. With over 600 staff across offices in South Africa, Kenya, the UK, Ireland, and the Netherlands, DVT provides a range of services including custom software development, mobile app development, Microsoft services, staff augmentation, AI solutions, and cloud application services. DVT partners with clients to transform their businesses through digital transformation and agile consulting. The company focuses on delivering IT solutions across various sectors such as retail, banking, insurance, education, and media. DVT is known for its expertise in software engineering and application modernization, providing agile teams and IT professionals to meet diverse technological needs.

📋 Description

• Design, build, and maintain robust ETL/ELT pipelines across AWS-native data environments • Own Airflow orchestration — scheduling, dependencies, retries, alerting, and operational support • Develop analytics-ready data models in dbt, using modular, warehouse-first transformation patterns • Work confidently across S3 (raw, staged, curated) and Redshift Serverless for storage and warehousing • Contribute to the roadmap and potential migration toward Snowflake as a future warehouse • Write clean, maintainable Python for pipeline logic, scripting, and lightweight engineering tasks • Embed data quality, testing, and observability into every pipeline — not as an afterthought • Engage directly with client stakeholders: gather requirements, present solutions, and advise on trade-offs • Partner with analysts, product teams, and other engineers in a distributed, remote-first setup

🎯 Requirements

• 5+ years in data engineering, analytics engineering, or closely related roles • Strong hands-on AWS data platform experience — S3-centred flows, cloud-native data workflows, warehouse-driven delivery • Apache Airflow — proven experience designing, maintaining, and troubleshooting production pipelines • dbt — solid analytics engineering patterns, modular models, testing, and documentation • Warehouse experience — Redshift preferred; Snowflake highly desirable; comparable warehouse backgrounds considered if adaptable • Python — confident scripting for pipelines, transformations, and automation • Strong understanding of data modelling (dimensional, wide tables, incremental strategies) • Excellent written and verbal communication — able to explain technical work credibly to non-technical audiences • Self-directed delivery in a fully remote, client-facing environment

🏖️ Benefits

• Continuous learning • Internal knowledge sharing • Sponsored technical events