Data Engineer

e&e is seeking a Data Engineer for an onsite contract opportunity in Philadelphia, PA! The Data Engineer is responsible for designing, developing, and optimizing scalable data pipelines and modern data infrastructure to support operational, analytical, and AI/ML initiatives. This role partners closely with data leadership, analytics engineering, business users, product teams, and data modelers to gather requirements, improve data quality, and ensure data is delivered in a reliable, secure, and timely manner. The ideal candidate brings strong experience across ETL/ELT development, data modeling, cloud-based data platforms, and modern data engineering tools, while maintaining compliance with data governance and security standards. Responsibilities: • Design and develop scalable, modern data infrastructure to support enterprise-wide data and analytics initiatives. • Build and maintain high-performance ETL/ELT pipelines and big-data processing solutions to reliably deliver curated data assets. • Optimize data pipeline performance and automate processes to enhance speed, reliability, and cost efficiency. • Collaborate with analytics engineering teams to capture and standardize key business metrics and KPIs. • Develop and maintain documentation including process flows, source-to-target mappings, error handling, and pipeline recovery procedures. • Ensure compliance with data governance policies, security standards, and industry regulatory requirements. • Drive continuous improvements to enhance automation, scalability, and overall data engineering best practices. • Partner with Operations teams to implement control objectives, manage data movement, and support incident management processes. • Perform additional data engineering duties as assigned. Requirements • Deep understanding of relational, dimensional, and non-relational data modeling techniques. • Extensive experience acquiring data through Change Data Capture (CDC), pub/sub patterns, real-time streaming (Kafka, Kinesis), APIs, and similar methods. • Hands-on experience building data pipelines using ETL/ELT tools (Talend, Informatica, Fivetran, Matillion, dbt), Python, Spark, SQL, etc., and delivering curated data in data lakes, enterprise data warehouses, and data marts. • Ability to analyze and interpret various data formats including XML, JSON, AVRO, and CSV. • Experience developing Data-as-a-Service (DaaS) APIs to deliver data products to internal or external consumers. • Strong SQL proficiency, including writing complex queries for data analysis, profiling, validation, and reconciliation. • Familiarity with data privacy and compliance regulations such as GDPR, CCPA, and HIPAA. • Experience working within Agile/Scrum teams. • Excellent analytical and problem-solving skills with a proactive approach to identifying and resolving issues. • Commitment to staying current with emerging data engineering technologies, cloud platforms, and best practices.