Lead Data Engineer

🕒 April 30

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Powerfleet

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1993

🤖 Artificial Intelligence

☁️ SaaS

🚗 Transport

Artificial Intelligence • SaaS • Transport

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

• Lead, hire, and develop a team of data engineers, including performance management and career growth • Own end-to-end delivery, including sprint planning, prioritization, and execution • Establish engineering standards and ensure high-quality, consistent output • Partner with cross-functional stakeholders to align data initiatives with business priorities • Design and evolve scalable data architecture across ingestion, transformation, storage, and consumption layers • Build and maintain high-volume ETL/ELT pipelines for real-time and batch data • Lead data modeling, governance, and data quality practices • Drive adoption of AI and automation across data engineering workflows • Partner with data science teams to operationalize models and embed AI into data products • Evaluate and implement emerging tools with a focus on practical impact

🎯 Requirements

• Bachelor’s degree with 8+ years (or Master’s with 5+) of relevant experience • 2+ years of experience managing or leading engineers • Proven experience running agile delivery and developing engineering talent • Strong stakeholder management and communication skills • Strong expertise in modern data architecture (data lakes, warehouses, lakehouse) • Experience with Snowflake and advanced SQL/data modeling (e.g., Kimball, star schema) • Proficiency in Python, SQL, and Spark (PySpark preferred) • Experience with streaming technologies such as Kafka • Hands-on experience with AWS (S3, Glue, EMR, Lambda, Redshift) • Familiarity with CI/CD, Infrastructure-as-Code (Terraform/CloudFormation), Airflow, Docker, and Kubernetes • Understanding of data governance, quality, and observability best practices

🏖️ Benefits

• health insurance • retirement plans • paid time off • flexible work arrangements • professional development