Lead Data Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Data Engineer based in the United States. This role offers the opportunity to lead the design and evolution of modern enterprise data platforms supporting analytics, reporting, and AI-driven initiatives. You’ll take ownership of scalable data architectures, ingestion frameworks, pipelines, and governed data products. The position combines hands-on engineering with technical leadership across data modeling, cloud platforms, governance, and reliability. You’ll work closely with AI/ML, platform engineering, security, analytics, and business teams to deliver trusted data solutions. A strong focus on observability, data quality, security, regulatory compliance, and operational resilience will be central to your work. You’ll also help establish standards and processes that make data more accessible, consistent, secure, and business-ready. This is a high-impact opportunity for an experienced data engineer who enjoys solving complex technical challenges and leading large-scale data initiatives.

Design, build, and maintain scalable lakehouse architectures and enterprise data platforms that support analytics, reporting, and AI-driven solutions. Lead end-to-end data engineering initiatives covering ingestion, transformation, storage, modeling, and analytics delivery. Develop secure and scalable data ingestion frameworks using CDC, batch, API, and file-based integrations from operational and transactional systems. Build and maintain reliable data pipelines and transformation workflows, with a strong focus on performance, recoverability, and operational resilience. Create data models, semantic layers, and governed metrics that provide consistent, trusted, business-ready data for downstream consumers. Implement data quality, reconciliation, observability, monitoring, and alerting processes to maintain reliable and high-performing pipelines. Establish and enforce data governance standards covering lineage, data contracts, quality thresholds, classification, access controls, and operational procedures. Partner with AI/ML, platform engineering, security, analytics, and business teams to develop governed data products and support regulatory and compliance requirements. Support the onboarding of new data sources, platforms, and environments while ensuring appropriate governance and operational controls. Contribute technical leadership and best practices across large-scale data initiatives, helping teams deliver scalable and maintainable solutions. Requirements 8+ years of professional experience in data engineering, including end-to-end ownership of data ingestion, transformation, storage, modeling, and analytics delivery. Demonstrated experience leading or contributing to large-scale data engineering initiatives and modern enterprise data platform development. Advanced proficiency in Python and SQL , including data modeling, transformation, data quality management, and performance optimization. Hands-on experience with modern lakehouse architectures and data platforms, including technologies such as Apache Iceberg, Delta Lake, Hudi, object storage, and cloud-native data solutions . Strong experience designing scalable data pipelines and change data capture solutions using technologies such as Kafka, Debezium, Airflow, Dagster, dbt , and enterprise integration frameworks. Strong understanding of data governance, lineage, security, access controls, observability, audit readiness, and compliance practices. Experience establishing data contracts, quality thresholds, operational procedures, and governance frameworks across enterprise data environments. Proven ability to collaborate effectively with AI/ML, analytics, platform engineering, security, and business stakeholders. Experience working with regulated or highly controlled data environments is valuable. Financial services or banking industry experience is highly preferred. Strong problem-solving, communication, technical leadership, and stakeholder-management skills. Benefits Full-time, fully remote position within the United States. Opportunity to lead the development of modern data platforms supporting analytics, AI, and enterprise business initiatives. High-impact technical role combining hands-on engineering with architectural and technical leadership. Exposure to modern lakehouse, cloud, data governance, AI/ML, and data observability technologies. Opportunity to collaborate with multidisciplinary teams across engineering, analytics, security, AI/ML, and business functions. Ability to influence enterprise data standards, architecture, governance, and engineering best practices. Compensation and additional benefits are not specified in the provided job description.

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