Data Engineer

Role: Data Engineer

Duration: 12 Months
Location: Reading, PA (Onsite)

Role Summary:

We are seeking a highly skilled Data Engineer to design, build, and optimize scalable data platforms that power analytics, machine learning, and business intelligence. This role requires deep expertise in data modeling, cloud-native architectures, and big data processing, along with the ability to lead complex data initiatives from design through production.

Key Responsibilities

• Design, develop, and maintain robust, scalable data pipelines using batch and streaming architectures.
• Build and optimize data models for analytical and operational use cases across relational and non-relational databases.
• Develop high-performance data processing solutions using Python and big data frameworks such as Pyspark, Kafka, and Hadoop.
• Implement and manage ETL/ELT workflows supporting data warehouses and data lakes.
• Architect and deploy data solutions on cloud platforms (AWS, Azure, or Google Cloud Platform) leveraging cloud-native services.
• Ensure data reliability, quality, security, and performance across the data ecosystem.
• Implement CI/CD pipelines and DevOps best practices for data engineering workloads.
• Orchestrate and monitor workflows using tools such as Apache Airflow.
• Perform performance tuning and cost optimization for large-scale data systems.
• Collaborate with analytics, data science, and application teams to enable data-driven solutions.
• Lead and support complex data initiatives, providing technical guidance and best practices.

Required Qualifications

• Advanced expertise in SQL, data modeling, and relational and non-relational databases.
• Strong programming skills in Python (Scala or Java as needed).
• Hands-on experience with big data and streaming technologies such as PySpark, Hadoop, and Kafka.
• Deep knowledge of cloud data platforms (AWS, Azure, or Google Cloud Platform) and cloud-native services.
• Strong experience with data warehouses, data lakes, and modern ETL/ELT tools.
• Experience with CI/CD, DevOps practices, and workflow orchestration tools (e.g., Airflow).
• Proven ability to troubleshoot, optimize, and scale high-volume data systems.
• Strong problem-solving skills and the ability to own and lead complex data initiatives.

Nice to Have

• Experience supporting real-time analytics or event-driven architectures
• Exposure to data governance, metadata management, or data quality frameworks
• Experience mentoring junior engineers or leading small technical teams