Senior Data Engineer

About The Role The Family Office is seeking a highly skilled Senior Data Engineer to design, build, and optimize scalable data platforms that support business intelligence, analytics, AI, and data-driven decision making across the organization. The successful candidate will be responsible for developing robust data pipelines, managing data infrastructure, ensuring data quality, and enabling seamless integration of data from multiple sources. This role requires strong technical expertise in cloud technologies, data warehousing, ETL/ELT processes, and modern data engineering practices. Key Responsibilities Data Engineering & Architecture • Design, develop, and maintain scalable data pipelines and data integration solutions. • Build and optimize data lakes, data warehouses, and data marts. • Develop batch and real-time data processing frameworks. • Design and implement data models that support reporting, analytics, and machine learning initiatives. • Establish best practices for data architecture, governance, and security. Data Platform Management • Manage and optimize cloud-based data platforms and infrastructure. • Monitor performance, reliability, and availability of data systems. • Ensure data quality, integrity, and consistency across platforms. • Implement automated data validation and monitoring processes. Analytics & Business Enablement • Collaborate with business stakeholders, analysts, and data scientists to understand data requirements. • Deliver high-quality datasets for dashboards, reporting, and predictive analytics. • Support AI and machine learning initiatives by creating reliable data pipelines. Development & Automation • Build and maintain ETL/ELT workflows. • Automate data ingestion and transformation processes. • Implement CI/CD practices for data engineering projects. • Optimize database performance and query efficiency. Leadership & Collaboration • Mentor junior data engineers and provide technical guidance. • Collaborate with technology, product, and business teams on strategic data initiatives. • Participate in architecture reviews and technology evaluations. Required Qualifications & Experience • Bachelor's degree in computer science, Data Engineering, Information Systems, or a related field. • 5-8+ years of experience in Data Engineering or related roles. • Strong proficiency in SQL and Python. • Experience building and managing large-scale data pipelines. • Hands-on experience with data warehousing solutions. • Strong understanding of data modeling and database design principles. • Experience working with cloud platforms such as AWS, Azure, or Google Cloud. The Family Office is an independent wealth management firm offering customized investment solutions in alternative asset classes, including private equity, private debt, and real estate. Serving high-net-worth individuals and families, we provide tailored strategies to address unique financial needs with a focus on transparency, diversification, and long-term value. With a commitment to excellence and decades of expertise, The Family Office helps clients preserve and grow their wealth across generations.

Bachelor's degree in computer science, Data Engineering, Information Systems, or a related field. 5-8+ years of experience in Data Engineering or related roles. Strong proficiency in SQL and Python. Experience building and managing large-scale data pipelines. Hands-on experience with data warehousing solutions. Strong understanding of data modeling and database design principles. Experience working with cloud platforms such as AWS, Azure, or Google Cloud.

Design, develop, and maintain scalable data pipelines and data integration solutions. Build and optimize data lakes, data warehouses, and data marts. Develop batch and real-time data processing frameworks. Design and implement data models that support reporting, analytics, and machine learning initiatives. Establish best practices for data architecture, governance, and security. Manage and optimize cloud-based data platforms and infrastructure. Monitor performance, reliability, and availability of data systems. Ensure data quality, integrity, and consistency across platforms. Implement automated data validation and monitoring processes. Collaborate with business stakeholders, analysts, and data scientists to understand data requirements. Deliver high-quality datasets for dashboards, reporting, and predictive analytics. Support AI and machine learning initiatives by creating reliable data pipelines. Build and maintain ETL/ELT workflows. Automate data ingestion and transformation processes. Implement CI/CD practices for data engineering projects. Optimize database performance and query efficiency. Mentor junior data engineers and provide technical guidance. Collaborate with technology, product, and business teams on strategic data initiatives. Participate in architecture reviews and technology evaluations.