Data Engineer

Overview We are seeking a passionate, innovative, and results-oriented Data Engineer to design and build scalable data solutions that empower business teams with reliable, actionable insights. This role will work within a large and complex data environment, developing data infrastructure, pipelines, and analytical solutions that provide timely and flexible access to business data. The ideal candidate combines strong SQL and Python expertise with hands-on ETL experience and the ability to translate business requirements into scalable data solutions. Key Responsibilities Design, build, and maintain scalable data pipelines and ETL processes. Develop and support analytical technologies that provide reliable and structured access to business data. Use SQL and Python to transform, analyze, and automate data workflows. Design and implement data solutions that support business intelligence, analytics, and reporting needs. Develop data models and structures that enable efficient reporting and analytics. Build and support reports and dashboards using business intelligence and reporting tools. Partner with business stakeholders to understand requirements and translate them into effective technical solutions. Apply data engineering best practices to improve scalability, reliability, data quality, and performance. Support data structures and pipelines operating at large scale while ensuring accuracy and consistency. Required Qualifications Bachelor’s degree. 3+ years of data engineering experience. Strong SQL proficiency and data analysis skills. Strong Python knowledge and hands‑on experience using Python for data engineering and automation. 3+ years of experience with data modeling, data warehousing, and ETL pipeline development. Experience developing and operating large-scale data structures for business intelligence and analytics. Ability to understand business requirements and translate them into scalable data solutions. Preferred Qualifications Experience with AWS technologies such as: Redshift S3 AWS Glue EMR Kinesis Firehose Lambda IAM roles and permissions Experience with non‑relational databases and data stores, including object storage, document or key‑value stores, graph databases, or column‑family databases. Strong experience with data modeling and data warehousing. Experience building and operating large-scale data structures for business intelligence and analytics. Experience with data quality automation, orchestration, and pipeline tooling beyond SQL. Top Skills SQL & Data Analysis – Advanced SQL fluency and ability to analyze complex datasets. Python – Strong Python development skills for automation, orchestration, and data engineering. ETL & Data Pipelines – Strong hands‑on experience designing, developing, and supporting ETL pipelines. Data Modeling & Warehousing – Experience creating scalable data structures that support analytics and reporting. AWS Data Technologies – Experience with cloud‑based data engineering services is highly valued. Leadership & Success Profile The Successful Candidate Will Demonstrate Deliver Results: Consistently deliver reliable, scalable data solutions that meet business needs and deadlines. Ownership: Take end‑to‑end responsibility for data pipelines, solutions, and outcomes while proactively identifying and resolving issues. Strong analytical and problem‑solving abilities. Ability to work independently while collaborating effectively with technical and business stakeholders. Attention to data quality, reliability, and operational excellence. Ability to operate effectively in a complex, large-scale data environment. #J-18808-Ljbffr IntePros