Senior Data Engineer / Analytics Engineer (AWS)
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DVT - Senior Data Engineer / Analytics Engineer (AWS)
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Senior Data Engineer / Analytics Engineer (AWS)
Remote
Johannesburg
,
Gauteng
,
South Africa
•
Centurion
,
Gauteng
,
South Africa
•
Gqeberha
,
Eastern Cape
,
South Africa
•
Remote
,
Gauteng
,
South Africa
•
Umhlanga
,
Kwazulu-Natal
,
South Africa
•
Johannesburg
,
Gauteng
,
South Africa
•
Cape Town
,
Western Cape
,
South Africa
•
+6 more
Data and Analytics & RPA (DAT)
Senior Data Engineer | Fully Remote | 2-yr contract. Modern AWS data stack — Airflow, dbt, Python, S3, Redshift, Snowflake. Join DVT on a high-impact fintech build.
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Job description
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.
Job requirements
DUTIES AND RESPONSIBILITIES
Data Platform & Pipelines
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
Engineering & Quality
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
Client & Collaboration
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
REQUIRED EXPERIENCE AND SKILLS
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
NICE TO HAVE
Snowflake
migration or implementation experience
Pipeline
monitoring and observability
(e.g. Datadog, Monte Carlo, CloudWatch, OpenLineage)
Experience implementing
data quality frameworks
(e.g. dbt tests, Great Expectations)
Background moving organisations from traditional warehouse-centric patterns toward modern
analytics engineering
Experience in
fintech, lending, or financial services
environments
Exposure to event-driven or streaming patterns (Kinesis, Kafka)
MINIMUM REQUIREMENTS
Matric (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
WHAT WE'RE NOT LOOKING FOR
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
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**Optional - Please describe your current role / project?
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Cape Town (Cape Town, Western Cape, South Africa)
Only open to candidates based in Cape Town
Centurion (Centurion, Gauteng, South Africa)
Gqeberha (Gqeberha, Eastern Cape, South Africa)
Johannesburg (Johannesburg, Gauteng, South Africa)
Remote (SA) (Remote, Gauteng, South Africa)
South Africa (Johannesburg, Gauteng, South Africa)
Umhlanga (Umhlanga, Kwazulu-Natal, South Africa)
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