Sr. Data Engineer / Lead - 67453

Hitachi • Reading, PA

10d

About The Position

Meet the Team You will be joining a high-performing Data Engineering & Analytics team focused on building scalable, cloud-native data platforms on AWS. The team works closely with Product Owners, Business Analysts, Data Scientists, and Analytics teams to deliver modern data solutions that enable advanced reporting, analytics, and business intelligence. The team is passionate about: Building scalable AWS-based data lake and analytics platforms Delivering reliable and high-performance ETL/ELT solutions Leveraging Talend Cloud 8.0, PySpark, and Spark SQL for enterprise-grade data processing Supporting real-time and batch data integration across multiple data sources Driving data quality, governance, automation, and operational excellence Implementing reusable frameworks and best practices for modern data engineering What You'll Be Doing As a Senior Data Engineer, you will play a key role in designing, developing, and optimizing enterprise data pipelines that power business-critical analytics and reporting solutions.

Requirements

• 10+ years of experience in Data Engineering, Big Data, ETL Development, or Data Integration
• Strong hands-on experience with Talend Cloud 8.0 / Talend ETL
• 6+ years of experience developing Python-based microservices
• 2+ years of hands-on experience with PySpark and Spark SQL
• 8+ years of experience working with AWS cloud services
• 3+ years of experience handling streaming data pipelines and real-time data processing
• Experience working on multiple enterprise-scale data engineering projects
• Talend Cloud 8.x development and administration
• PySpark development and Spark SQL optimization
• Python programming and reusable framework development
• AWS Services including: Amazon S3, AWS Glue, AWS Lambda, Amazon Athena, Amazon EMR
• Data Lake architecture and implementation
• ETL/ELT design patterns and best practices
• Streaming technologies and event-driven architectures
• Data modeling, transformation, and schema management
• Performance tuning and optimization of Spark workloads
• Data quality, monitoring, and operational support
• Strong analytical and problem-solving capabilities
• Ability to build scalable, production-grade data solutions
• Excellent communication and stakeholder management skills
• Experience working in Agile delivery environments
• Strong collaboration skills across engineering, analytics, and business teams
• Ability to mentor junior engineers and contribute to engineering best practices

Responsibilities

• Design, develop, and maintain ETL/ELT workflows using Talend Cloud 8.0
• Build scalable data ingestion pipelines from APIs, flat files, databases, and streaming sources
• Develop and support large-scale data processing solutions using PySpark and Spark SQL
• Design and manage AWS-based data lake architectures utilizing Amazon S3
• Develop cloud-native data solutions leveraging AWS services such as: AWS Glue, AWS Lambda, Amazon Athena, Amazon EMR
• Build and support Python-based microservices for data integration and processing workloads
• Implement and maintain streaming data pipelines for near real-time data processing
• Optimize Spark jobs, ETL workflows, and AWS workloads for performance, scalability, and cost efficiency
• Ensure data quality, reliability, governance, and operational monitoring across the platform
• Collaborate with business stakeholders, architects, analysts, and development teams to deliver high-quality data solutions
• Troubleshoot production issues and continuously improve platform performance and reliability

Benefits

• industry-leading benefits, support, and services that look after your holistic health and wellbeing
• flexible arrangements that work for you (role and location dependent)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed