Data Analyst

Location Columbus, OH (Onsite) Job Summary STAFFXPERT LLC is seeking a Lead Data Engineer on behalf of our client in Columbus, OH. This role is ideal for a highly skilled data professional with extensive experience designing, building, and optimizing enterprise-scale data pipelines and data platforms. The successful candidate will work closely with business stakeholders, data scientists, analysts, and governance teams to deliver scalable data solutions that support analytics, reporting, and data-driven decision-making. This position requires strong expertise in modern data engineering practices, cloud-based technologies, data architecture, and large-scale data integration. Key Responsibilities Design, develop, and maintain scalable and efficient data pipelines and data integration solutions. Architect and implement enterprise data platforms that support business intelligence, analytics, and data science initiatives. Collaborate with data scientists, business analysts, and stakeholders to gather requirements and deliver data solutions aligned with business objectives. Build, optimize, and manage data ingestion, transformation, and processing workflows across diverse data sources. Ensure data quality, consistency, governance, and compliance across data assets. Partner with data governance teams to promote reusable and governed data products. Implement data testing, monitoring, and performance optimization strategies. Support DevOps and CI/CD practices, including version control, automated testing, deployment, and release management. Mentor junior team members and provide technical leadership across projects. Lead cross-functional initiatives and contribute to enterprise data strategy and best practices. Required Qualifications Bachelor's degree in Computer Science, Information Systems, Statistics, Engineering, or a related field. 7+ years of experience in Data Engineering, Data Integration, Data Management, or related disciplines. 7+ years of hands-on experience with database development, SQL programming, ETL/ELT processes, and advanced analytics environments. Strong experience designing, building, and optimizing large-scale data pipelines and data architectures. Experience working with large, complex, and heterogeneous datasets. Solid understanding of data modeling, data governance, data quality, and data management best practices. Experience with cloud-based data engineering technologies and platforms. Knowledge of DevOps methodologies, CI/CD pipelines, version control systems, and automated testing practices. Strong analytical, problem-solving, and communication skills. Proven ability to lead initiatives and collaborate effectively with technical and non-technical stakeholders. Preferred Qualifications Master's degree in Computer Science, Statistics, Data Science, or a related field. Hands-on experience with data testing and validation frameworks. Experience with data preparation and data wrangling tools. Strong experience with AWS data engineering services, including AWS Glue, AWS Lambda, Amazon Athena, Amazon S3, and Amazon Redshift. Experience with business intelligence and reporting tools such as Power BI, Tableau, or similar platforms. Familiarity with open-source and commercial data science platforms. Experience working in Agile delivery environments. Demonstrated success leading cross-functional teams and mentoring junior professionals. Experience within the Financial Services, Banking, Insurance, or FinTech industry is highly preferred. #J-18808-Ljbffr