Senior Data Engineer

Job not on LinkedIn

🔥 0 minutes ago

🇿🇦 South Africa – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 10%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Powerfleet

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1993

📦 Logistics

💼 Consulting

🤖 Artificial Intelligence

Logistics • Consulting • Artificial Intelligence

Powerfleet is a global AIoT and SaaS-based mobile asset management company that provides end-to-end solutions to monitor, manage, and optimize connected vehicles and warehouse assets. The company ingests and harmonizes data from diverse sources to deliver actionable insights that improve safety, efficiency, and sustainability across the supply chain. Powerfleet serves millions of subscribers and thousands of enterprise customers worldwide, positioning itself as a B2B technology provider for intelligent mobility and operational optimization.

📋 Description

• Design and build new data products and platforms on high-volume telematics and IoT data using Snowflake and AWS • Design and maintain high-volume batch and event-driven ingestion, transformation, and integration processes across SQL Server, Snowflake, and AWS • Implement incremental loads, change tracking, deduplication, late-arriving data handling, and reconciliation • Make retries, recovery, and backfills safe and repeatable • Investigate failed or delayed processing, blocking, deadlocks, and backlogs • Identify root causes and improve reliability and throughput • Optimise SQL, stored procedures, execution plans, indexing, partitioning, and concurrent processing • Use Snowflake query profiles, pruning, clustering, and warehouse configuration to improve efficiency • Design maintainable data models and integration patterns • Write and review production code, automate deployments, and validate data correctness, performance, and concurrent behaviour • Define rollback and recovery procedures • Establish monitoring and alerts for failures, freshness, completeness, backlog, and throughput • Maintain pipeline documentation, dependency maps, runbooks, and support handovers • Translate business requirements into practical solutions and coordinate priorities and dependencies • Mentor engineers, review designs, and contribute to team development and recruitment • Strengthen testing, security, access controls, and development standards • Apply AI-assisted development and automation with human review, testing, and appropriate data protection • Collaborate with data engineers, BI specialists, and product teams to shape technical decisions and deliver reliable solutions

🎯 Requirements

• A relevant degree or tertiary qualification in Computer Science, Engineering, Information Technology, Data Engineering, or a related discipline, or equivalent practical professional experience • 4–8 years of hands-on Data Engineering experience, including experience building and supporting production data pipelines • Strong practical experience working with SQL and Python in production environments • Proven experience with modern cloud and data platforms, ideally including AWS and Snowflake • Solid understanding of data modelling, database design, performance optimisation, and data engineering best practices • Experience with Git, code reviews, testing, and CI/CD • Strong analytical and problem-solving skills for complex data and production issues • Experience mentoring engineers, contributing to technical discussions, or reviewing technical designs is advantageous • Familiarity with Microsoft Azure is an advantage • Experience with telematics, IoT, time-series or high-volume operational data is beneficial • Experience with multi-tenant systems and customer-facing reporting is beneficial • Experience with Kafka, Kinesis, Spark/PySpark, Iceberg, Delta Lake, or Hudi is beneficial • Experience with Airflow, dbt, and automated database deployment tooling is beneficial • Experience with SQL Server tooling such as T-SQL, SSIS, and SQL Agent is beneficial • Experience with C#, API integration or maintenance, Redshift, or other cloud data platforms is beneficial • Experience with data lineage, catalogues, data contracts, and practical governance is beneficial • Experience working within GDPR or POPIA requirements is beneficial

🏖️ Benefits

• Equal opportunity employer committed to employment equity, diversity, and inclusion • Reasonable accommodation throughout the recruitment process • People-first, people-centric culture • Opportunity to work on modern cloud and data platforms at IoT scale • Mentoring, technical guidance, and shared ownership opportunities

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