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Powerfleet

Senior Data Engineer

Remote, United States

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Job details

Experience: 4–8 years of hands-on Data Engineering experience, including experience building and supporting production data pipelines.
Posting language: English
Posted: Nov 9, 2026

Original job description

About Powerfleet Powerfleet (Nasdaq: AIOT; JSE: PWR) is a global leader in the artificial intelligence of things (AIoT) software-as-a-service (SaaS) mobile asset industry. With more than 30 years of experience, Powerfleet unifies business operations through the ingestion, harmonization, and integration of data - regardless of source - and delivers actionable insights to help companies meet their strategic objectives around Safety, Compliance, Efficiency and Sustainability. Our people-first culture and relentless innovation empower customers to achieve measurable, sustainable business improvements. Powerfleet serves over 2.6 million subscribers across more than 48,000 customers in 120 countries, with commercial operations across every major continent. We are looking for an experienced data engineer to design, build and improve the pipelines and platforms that support operational reporting, analytics and data products. You will write production code, solve complex data and performance problems, and take responsibility for reliable delivery across established and cloud-based systems. Working closely with data engineers, BI specialists and product teams, you will help shape technical decisions, review changes and develop engineering capability through practical guidance and shared ownership What you will do

Build at IoT scale. Design and build new data products and platforms on high-volume telematics and IoT data, using modern technology such as Snowflake and AWS to turn billions of events into insight customers rely on.
Build and improve data pipelines. Design and maintain high-volume batch and event-driven ingestion, transformation and integration processes across SQL Server, Snowflake and AWS.
Protect data correctness. Implement reliable incremental loads, change tracking, deduplication, late-arriving data handling and reconciliation. Make retries, recovery and backfills safe and repeatable.
Resolve production problems. Investigate failed or delayed processing, blocking, deadlocks and backlogs. Identify root causes and implement lasting improvements to reliability and throughput.
Tune performance and cost. Improve SQL, stored procedures, execution plans, indexing, partitioning and concurrent processing. Use Snowflake query profiles, pruning, clustering and warehouse configuration to improve efficiency.
Evolve the platform. Design maintainable data models and integration patterns. Improve existing systems through controlled changes while contributing to platform modernisation where it adds clear value.
Deliver safe changes. Write and review production code, automate deployments and validate data correctness, performance and concurrent behaviour. Define appropriate rollback and recovery procedures.
Make operations visible. Establish useful monitoring and alerts for failures, freshness, completeness, backlog and throughput. Maintain pipeline documentation, dependency maps, runbooks and support handovers.
Support effective delivery. Translate business requirements into practical solutions, explain trade-offs and coordinate priorities and dependencies. Mentor engineers, review designs and contribute to team development and recruitment.
Improve engineering practices. Strengthen testing, security, access controls and development standards. Apply AI-assisted development and automation where useful, with human review, testing and appropriate protection of company data.

Qualifications & Experience

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 working 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 working within modern engineering practices, including Git, code reviews, testing, and CI/CD.
Strong analytical and problem-solving skills, with the ability to troubleshoot complex data and production issues.
Experience mentoring engineers, contributing to technical discussions, or reviewing technical designs is advantageous.

Nice to have

Experience with one or more of the following would be beneficial:
Familiarity with Microsoft Azure is an advantage.
Telematics, IoT, time-series or other high-volume operational data; multi-tenant systems and customer-facing reporting.
Kafka, Kinesis or equivalent streaming platforms; Spark/PySpark and lakehouse formats such as Iceberg, Delta Lake or Hudi.
Airflow, dbt and automated database deployment tooling.
SQL Server-specific tooling such as T-SQL, SSIS and SQL Agent; C# and API integration or maintenance; Redshift or other cloud data platforms.
Data lineage, catalogues, data contracts and practical governance, including experience working within GDPR or POPIA requirements

EEO/ BEE Statement Powerfleet is an equal opportunity employer committed to employment equity, diversity, and inclusion. In alignment with the Employment Equity Act 1998 and our Employment Equity plan, we actively encourage applications from designated groups, including Black people, women, and individuals with disabilities. As part of our commitment to transformation and in accordance with the Broad-Based Black Economic Empowerment Act, preference may be given to candidates from designated groups where appropriate. All qualified applicants will be considered based on merit, skills, and experience. We are committed to providing reasonable accommodation throughout the recruitment process. If you require support or adjustments, please let us know.

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