Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Lead Data Engineer focusing on real-time streaming and event-driven systems in Reading, PA (Hybrid). Contract length and pay rate are unspecified. Key skills include Apache Kafka, Spark, Flink, AWS, and IoT platform experience. AWS certification preferred.
🌎 - Country
United States
πŸ’± - Currency
$ USD
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πŸ’° - Day rate
600
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πŸ—“οΈ - Date discovered
September 24, 2025
πŸ•’ - Project duration
Unknown
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🏝️ - Location type
Hybrid
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πŸ“„ - Contract type
Unknown
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Reading, PA
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🧠 - Skills detailed
#Debugging #Programming #Apache Kafka #Data Ingestion #DevOps #IoT (Internet of Things) #Cloud #Data Lake #Leadership #Redshift #Kafka (Apache Kafka) #Python #Apache Spark #AWS Kinesis #Data Engineering #PySpark #Data Architecture #S3 (Amazon Simple Storage Service) #Spark (Apache Spark) #Java #Scala #Data Processing #Lambda (AWS Lambda) #AWS (Amazon Web Services) #Storage
Role description
Job Title: Lead Data Engineer– Real-Time Streaming & Event-Driven Systems (If worked in similar project on real time streaming it is plus) Location: Reading, PA (Hybrid) Role Overview: We are looking for a seasoned Lead Data Engineer with deep hands-on expertise in designing and delivering event-driven architectures and real-time streaming systems. The ideal candidate will have extensive experience with Apache Kafka, Apache Spark Structured Streaming, Apache Flink, and messaging queues, and a strong background in building highly resilient IoT data platforms on AWS. Key Responsibilities: Architecture & Design β€’ Design event-driven systems using Kafka, Flink, and Spark Structured Streaming. β€’ Define data models, schemas, and integration patterns for IoT and telemetry data. Technical Leadership β€’ Lead the technical direction of the data engineering team, ensuring best practices in streaming architecture and cloud-native design. β€’ Provide hands-on guidance in coding, debugging, and performance tuning of streaming applications. β€’ Collaborate with product, engineering, and DevOps teams to align data architecture with business needs. Implementation & Delivery β€’ Build and deploy real-time data processing solutions using Apache Flink and Spark Structured Streaming. β€’ Integrate messaging systems (Kafka, Kinesis, RabbitMQ, etc.) with cloud-native services on AWS. β€’ Ensure high availability, scalability, and resilience of data platforms supporting IoT and telemetry use cases. Innovation & Optimization β€’ Continuously evaluate and improve system performance, latency, and throughput. β€’ Explore emerging technologies in stream processing, edge computing, and cloud-native data platforms. β€’ DevOps,CI/CD, and infrastructure-as-code practices. Required Technical Skills: β€’ Mandatory Expertise: β€’ Apache Flink (real-time stream processing) β€’ Apache Spark Structured Streaming β€’ Apache Kafka or equivalent messaging queues (e.g., RabbitMQ, AWS Kinesis) β€’ Event-driven architecture design β€’ AWS services: S3, Lambda, Kinesis, EMR, Glue, Redshift β€’ Additional Skills: β€’ Strong programming skills in Pyspark, Java, or Python β€’ Experience with containerization (OpenShift) β€’ Familiarity with IoT protocols and resilient data ingestion patterns β€’ Knowledge of data lake and lakehouse architectures(Iceberg) S3 storage Preferred Qualifications: β€’ Experience in building large-scale IoT platforms or telemetry systems. β€’ AWS Certified Data Analytics or Solutions Architect.