Data Engineer

Job Title: Data Engineer Location: San Jose, California, USA (Hybrid – Minimum 3 days onsite) Duration: 12 monthsSchedule: 40 hours per week | 8 hours per day | Monday to Friday Compensation: Up to $65.49 USD per hour (W2) Employment Type: Contract (W2 only – No H-1B / No Subcontracting) Position Overview The Financial Data Engineer will be responsible for designing and developing analytical solutions that provide deep insights into financial performance metrics and customer journey data. This position requires a technically skilled professional who can combine advanced data engineering practices with strong business acumen to enable self-service analytics, enhance data reliability, and deliver high-quality outcomes within established timelines. Key Responsibilities • Design, implement, and maintain analytical data models to support financial and business decision-making. • Develop scalable data pipelines and ETL processes to source, transform, and integrate data from multiple systems, including SAP HANA, SQL Server, and other relational databases. • Collaborate with cross-functional teams to refine data models, ensuring alignment with evolving business and technical requirements. • Create and maintain comprehensive documentation, including data design, architecture, and workflow specifications. • Participate in technical reviews, discovery sessions, and modeling exercises to ensure data quality and consistency. • Monitor, troubleshoot, and optimize performance across data services and applications to ensure stability and scalability. • Support analytical reporting initiatives for sales, bookings, finance, and subscription-based business areas. • Drive automation and efficiency in data management through scripting, orchestration, and workflow optimization tools. Required Qualifications • Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related discipline. • Minimum of 5 years of professional experience in data engineering or data analytics. • Proven expertise in Python, SQL/PLSQL, and Azure Databricks. • Demonstrated experience in enterprise data warehousing, data modeling, and performance optimization. • Proficiency in ETL design, development, and testing, including data warehouse metadata modeling and automation. • Familiarity with Airflow or equivalent orchestration tools. • Exposure to BI platforms such as Tableau and Power BI. • Solid understanding of system operations, including capacity management, performance tuning, and troubleshooting (CPU, memory, storage, and network fundamentals). • Strong problem-solving, analytical, and communication skills with a customer-oriented mindset. Preferred Skills • Experience developing analytics solutions for financial, sales, or subscription business domains. • Advanced understanding of cloud data architectures and data governance practices. • Ability to work effectively under tight deadlines with minimal supervision while maintaining attention to detail.