Senior Data Engineer / Analytics Engineer (AWS)
Quick Summary
DVT is one of the top software development companies on the continent. Our engineers consult on cutting-edge platforms at leading companies across South Africa and globally.
Snowflake migration or implementation experience Pipeline monitoring and observability (e.g. Datadog, Monte Carlo, CloudWatch, OpenLineage) Experience implementing data quality frameworks (e.g.
DVT is one of the top software development companies on the continent. Our engineers consult on cutting-edge platforms at leading companies across South Africa and globally. You'll work alongside some of the most established practitioners in the country, on the latest technologies in the modern data stack.
We are proud of our culture of continuous learning, internal knowledge sharing, and sponsored technical events across the AWS and data ecosystem.
We are looking for a Senior Data Engineer / Analytics Engineer to join our Data and Automation practice on a high-impact client engagement. You will help design, build, and operate a modern AWS-first data platform — moving data through S3 into Redshift Serverless, orchestrated by Airflow, modelled with dbt, and scripted in Python, with a likely evolution towards Snowflake.
This is a client-facing role in a fully remote environment. You will own pipelines end to end, shape analytics engineering practices, and communicate clearly with distributed stakeholders.This is not a generic backend engineering role. Strong software engineers are only relevant where they bring credible, hands-on experience in a modern cloud data platform.
Responsibilities
~1 min readDesign, 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
Apply sound version control, code review, and CI/CD practices to data workloads
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
Contribute to architectural reviews, retrospectives, and continuous improvement of platform practices
Nice to Have
~1 min readExperience in fintech, lending, or financial services environments
Exposure to event-driven or streaming patterns (Kinesis, Kafka)
Requirements
~1 min readMatric (Grade 12) certificate
Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related field (or equivalent practical experience)
AWS certification advantageous (e.g. Data Engineer – Associate, Solutions Architect – Associate/Professional)
Reliable home-office setup and connectivity suitable for a fully remote client engagement
Pure backend / application-only engineers with no production data platform work
Candidates with no real orchestration experience
Candidates with no warehouse or data modelling background
Profiles without AWS exposure
Candidates who cannot clearly articulate the data work they've shipped
Location & Eligibility
Listing Details
- First seen
- May 6, 2026
- Last seen
- May 29, 2026
Posting Health
- Days active
- 23
- Repost count
- 0
- Trust Level
- 23%
- Scored at
- May 29, 2026
Signal breakdown
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