Piper Companies is seeking a Lead Data Engineer to support a company focused on enterprise digital transformation and advanced cloud‑based data modernization initiatives. This position is hybrid in Ft. Washington, PA. The Sr Data Engineer will provide strategic direction for enterprise‑wide data architecture and cloud infrastructure. This role enables the organization to leverage data as a competitive advantage by driving innovation, adopting emerging technologies, and shaping long‑term architectural vision. Responsibilities for the Lead Data Engineer include: • Defining enterprise‑level data architecture and infrastructure strategies • Designing advanced data warehouses, data lakes, and hybrid cloud architectures • Driving adoption of automation, DevOps, and CI/CD best practices for data platforms • Partnering with executive leadership to align data infrastructure with business strategy • Guiding cloud resource planning, cost optimization, and capacity management Required Qualifications for the Lead Data Engineer include: • 7+ years of experience in data engineering, cloud data ecosystems, and infrastructure strategy • Expertise with cloud‑based data tools such as Azure Fabric, Data Factory, Synapse, or similar • Proficiency in Python, SQL, ETL development, and data integration architecture • Strong understanding of Azure security controls, resource management, and governance frameworks • Bachelor’s Degree in Business, Computer Science, Finance, Information Systems, or related field Compensation for the Lead Data Engineer includes: Salary Range: $140,000-$150,000 depending on experience Full Benefits Package: PTO, Paid Holidays, Medical, Dental, Vision, 401K, Tuition Reimbursement, Sick leave as required by law #LI-SM2 #LI-HYBRID SEO Keywords Enterprise Data Architect, Cloud Infrastructure Architect, Azure Data Lead, Data Warehouse Architect, Data Lake Architect, Azure Synapse, Azure Fabric, Data Governance Lead, Cloud Strategy Architect, DevOps for Data, CI/CD Data Engineering, Python Data Engineer, Cloud Security Governance, Enterprise Architecture, Data Modernization