Find & Apply For Software Developer / Engineer Jobs in Erie, Pennsylvania

Senior Full-Stack Data Engineer Job Overview We are seeking an experienced Senior Full-Stack Data Engineer with 10-15 years of hands-on experience in data engineering, data architecture, and cloud-native data platforms. The ideal candidate will have strong expertise in AWS, SQL, Python, PySpark, ETL/ELT, and modern data technologies . This role will be responsible for designing, developing, optimizing, and supporting next-generation data platforms at scale. The candidate will also provide technical leadership, contribute to architectural decisions, mentor team members, and deliver high-impact data solutions in a fast-paced environment. Key Responsibilities Design and develop scalable data pipelines, ETL/ELT frameworks, and cloud-based data platforms . Architect and optimize data solutions using AWS services and modern data engineering technologies . Build and maintain high-volume, petabyte-scale data infrastructure in cloud-native environments. Develop robust data processing solutions using Python, PySpark, and SQL . Work with data lake and lakehouse technologies, including Apache Iceberg and AWS Glue Catalog . Develop and optimize data models and transformations using dbt Core . Work with data warehouses and query engines such as Snowflake, Redshift, and Athena . Implement and support data integration solutions using Talend and AWS services. Leverage AWS streaming technologies for near-real-time data processing. Implement appropriate security, access controls, networking, and governance using

AWS IAM, VPC, S3

, and related services. Use Git and modern development practices for source control, collaboration, and CI/CD. Monitor and troubleshoot data platforms and pipelines using tools such as Splunk . Collaborate with architects, developers, analysts, and business stakeholders to deliver reliable data solutions. Provide technical leadership, code reviews, mentoring, and guidance to other data engineers. Required Skills & Experience 10-15 years of progressive experience in Data Engineering, Data Architecture, or Full-Stack Data Engineering. Strong understanding of data engineering principles, ETL/ELT patterns, data modeling, metadata management, and data governance . Extensive hands-on experience with AWS , particularly S3, IAM, VPC, Glue, Athena, and related services. Strong programming skills in Python and PySpark . Advanced SQL skills with experience in performance tuning and complex data transformations. Experience with Talend, dbt Core, Apache Iceberg, and AWS Glue Catalog . Hands-on experience with Snowflake, Amazon Redshift, and Amazon Athena . Experience with AWS streaming services and large-scale data processing. Strong understanding of Git, CI/CD, and software engineering best practices . Experience designing and managing large-scale or petabyte-scale data platforms . Strong problem-solving, communication, and technical leadership skills. Preferred Qualifications Experience in the insurance industry or other data-intensive enterprise environments . Experience with cloud-native data lake/lakehouse architecture. Knowledge of data security, governance, lineage, and metadata management. Experience mentoring engineers and driving technical architecture decisions. Bachelor s or Master s degree in Computer Science, Engineering, or a related field is preferred.