Senior Data Engineer

Are you passionate about building scalable data platforms, designing modern data pipelines, and transforming complex data into powerful business insights? We are seeking a highly skilled Senior Data Engineer to join a dynamic technology team focused on developing robust data solutions that support enterprise integrations, analytics, and data-driven decision‑making. This role is ideal for a hands‑on professional who enjoys solving complex data challenges, collaborating across teams, and delivering high‑performance cloud‑based data solutions. Key Responsibilities Design, develop, and optimize scalable, reliable, and high‑performing data pipelines and integration solutions. Partner with cross‑functional teams to deliver enterprise data integration initiatives with a strong focus on resilience, scalability, and operational excellence. Collaborate with business stakeholders to gather requirements, define technical solutions, and provide effort estimations. Develop and maintain automated testing, deployment, and monitoring processes for data pipelines. Troubleshoot data‑related issues, provide technical support, and ensure smooth operation of data platforms and integrations. Create and maintain comprehensive technical documentation, including data flows, lineage, architecture, and operational procedures. Support production environments by assisting with advanced issue resolution and performance optimization. Ensure high standards of data quality, accuracy, and consistency across enterprise data assets. Perform data analysis and root‑cause investigations to identify and resolve data anomalies. Conduct peer code reviews and mentor junior team members on engineering best practices. Implement data governance, security, and master data management standards throughout the data lifecycle. Qualifications Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or an equivalent combination of education and experience. 5–8 years of experience designing and developing data pipelines, system integrations, and enterprise data solutions. At least 3 years of experience working with modern cloud‑based data platforms and technologies. Strong experience building and managing lakehouse architectures using modern cloud data technologies. Proven expertise designing layered data architectures that support analytics‑ready datasets and governed data consumption. Experience implementing both batch and streaming data processing solutions. Hands‑on knowledge of ETL/ELT pipeline orchestration frameworks and workflow management tools. Advanced proficiency in SQL and Python‑based data engineering solutions. Strong understanding of data modeling methodologies, including dimensional modeling and analytical schema design. Experience optimizing data platform performance through partitioning, clustering, workload tuning, and query optimization. Knowledge of data governance, security controls, metadata management, lineage tracking, and access management. Familiarity with CI/CD practices, source control systems, automated testing, and deployment pipelines. Experience working with cloud ecosystems and data services across major cloud platforms. Exposure to AI, machine learning, or generative AI enablement within modern data environments is a plus. Excellent communication, collaboration, and stakeholder management skills. What Success Looks Like Delivering scalable and reliable data solutions that support enterprise‑wide analytics and integration initiatives. Building efficient, maintainable, and automated data pipelines that meet evolving business needs. Ensuring data quality, governance, and security standards are consistently maintained. Collaborating effectively with technical and business teams to drive successful project outcomes. Mentoring team members and contributing to continuous improvement across engineering practices. Enabling business users with trusted, accessible, and analytics‑ready data. Performance‑based bonus opportunities. Comprehensive health and wellness benefits. Retirement savings plans with employer contributions, where applicable. Tuition reimbursement and professional development support. Mobility and work‑related allowances. Paid holidays and generous time‑off programs. Community involvement and volunteer opportunities. A collaborative environment that supports innovation, growth, and career advancement. #J-18808-Ljbffr