Data Engineer

Overview The Data Modeler role is critical in designing and implementing robust data warehousing solutions. Candidate will collaborate closely with product managers, business stakeholders, and the development community to ensure data models meet business needs and support efficient data management. This role requires a blend of technical expertise in data modeling methodologies and strong communication skills to translate complex concepts for both technical and non-technical audiences. Responsibilities Leads story refinement and delivery of requirements through the delivery lifecycle and assists team members in resolving technical complexities. Codes complex solutions to integrate, clean, transform, and control data, builds processes supporting data transformation, data structures, metadata, data quality controls, dependency, and workload management, assembles complex data sets, and communicates required information for deployment. Leads documentation of system requirements, collaborates with development teams to understand data requirements and feasibility, and leverages architectural components to develop client requirements. Leads testing teams to develop test plans, contributes to existing test suites including integration, regression, and performance, analyzes test reports, identifies test issues and errors, and leads triage of underlying causes. Leads work efforts with technology partners and stakeholders to close gaps in data management standards adherence, negotiates pathways by thinking creatively to identify and communicate solutions to complex problems, and leverages knowledge of information systems, techniques, and processes. Leads complex information technology projects to ensure on-time delivery and adherence to release processes and risk management and defines and builds data pipelines to enable data-informed decision making. Mentors Data Engineers to enable continuous development and monitors key performance indicators and internal controls. Partners with product managers and business representatives to understand data requirements and translate them into comprehensive data models (conceptual, logical, and physical). Ensures data models adhere to industry standards and best practices, promoting data quality and minimizing redundancy. Documents, communicates, and centrally manages data models for efficient access and reference. Designs technical data solutions aligned with business needs, providing clear guidance to development teams. Collaborates with technical teams to troubleshoot complex SQL queries within ETL processes. Leverages Business Intelligence tools to visualize insights gleaned from data models. Actively participates in discussions and meetings, effectively communicating technical concepts to audiences with varying technical backgrounds. Designs scalable, high-performance data models to support enterprise data warehousing and analytics. Ensures adherence to data modeling standards, governance, and best practices to maintain data quality and minimize redundancy. Develops and maintains data model documentation and metadata for centralized access and reuse. Partners with architects and development teams to deliver business-aligned technical data solutions. Provides support to ETL/data engineering teams, including SQL troubleshooting and data issue resolution. Enables reporting and analytics by supporting BI tools and data visualization needs. Participates in agile ceremonies and design reviews to align with delivery goals. Communicates complex data concepts effectively to technical and non-technical stakeholders. Required Qualifications 10+ years of experience with Data Engineering. 3+ years hands‑on experience in Scala. 3+ years of hands‑on experience in Spark. Expertise in data modeling methodologies (3NF, dimensional, data vault) for enterprise‑level data stores. Strong understanding of data architecture concepts (data warehouse, data mart, ODS, ETL, reporting, analytics). Experience with relational and NoSQL database design (SQL Server, Oracle, Object Storage, MongoDB, Elasticsearch, etc.). Proficiency in data analysis and modeling tools (Power Designer, Erwin, etc.). Hands‑on experience with SQL and/or PL/SQL. Experience with Business Intelligence tools (Power BI, Tableau, etc.). Excellent communication and interpersonal skills for seamless collaboration with diverse stakeholders. Desired Qualifications Knowledge of payments industry data standards (ISO 20022) and regulatory experience within payments domain. Understanding of Apache Hadoop and the Hadoop ecosystem. Familiarity with data Lakehouse data modeling skills. Skills Analytical Thinking Application Development Data Management DevOps Practices Solution Design Agile Practices Collaboration Decision Making Risk Management Test Engineering Architecture Business Acumen Data Quality Management Financial Management Solution Delivery Process Shift 1st shift (United States of America) Hours Per Week 40 #J-18808-Ljbffr