Big Data Integration / IoT Tech Lead
Location: Reading, PA (Remote)
Job Summary
We are seeking an experienced Big Data Integration / IoT Tech Lead to drive the design, development, and implementation of scalable IoT solutions and big data pipelines. The ideal candidate will lead a team of engineers, architect end-to-end data integration strategies, and ensure high-quality, real-time analytics for IoT devices and enterprise systems.
Key Responsibilities
- Lead the architecture, design, and implementation of IoT platforms and big data integration solutions.
- Design and implement data ingestion pipelines from IoT devices and external data sources into big data ecosystems (Hadoop, Spark, Kafka, AWS/Google Cloud Platform/Azure).
- Ensure real-time data processing, event streaming, and batch processing for high-volume IoT datasets.
- Define data models, storage strategies, and APIs for integration with enterprise systems and analytics platforms.
- Lead, mentor, and guide a team of software engineers, data engineers, and IoT developers.
- Collaborate with product managers, data scientists, and business stakeholders to understand requirements and translate them into scalable technical solutions.
- Ensure robust security, data privacy, and compliance standards for IoT and big data platforms.
- Conduct performance tuning, optimization, and troubleshooting of data pipelines and IoT applications.
- Implement monitoring, logging, and alerting for IoT devices and data pipelines.
- Stay updated with emerging trends in IoT, big data, edge computing, and cloud technologies.
Required Skills & Qualifications
- Proven experience in IoT platforms, big data integration, and real-time analytics.
- Strong programming skills: Java, Python, Scala, or Node.js.
- Experience with big data technologies: Hadoop, Spark, Kafka, Flink, or similar.
- Hands-on experience with cloud platforms: AWS IoT Core, Azure IoT Hub, or Google Cloud IoT.
- Knowledge of RESTful APIs, MQTT, CoAP, OPC-UA, and other IoT communication protocols.
- Strong understanding of data modeling, ETL/ELT processes, and streaming analytics.
- Experience in deploying and scaling distributed systems and microservices.
- Strong leadership, mentoring, and project management skills.
- Excellent problem-solving and communication skills.
Preferred
- Experience with AI/ML integration for IoT analytics.
- Knowledge of edge computing frameworks and sensor data analytics.
- Familiarity with DevOps practices and containerization (Docker, Kubernetes).