Lead Data Engineer (No C2C)

Title: Lead Data Engineer Location: New York (Onsite) The Role As the Lead Data Engineer, you will: • Own the design, implementation, and operation of our core data platform (warehouse, pipelines, ingestion, CDC). • Lead projects • Partner with analytics, data science, product, and business stakeholders to translate business needs into data solutions. • Drive architecture decisions and roadmap for data ingestion, transformation, storage, and serving layers. • Ensure our platform supports both batch and near-real-time data flows — particularly around change-data-capture for source systems. • Design and maintain orchestration workflows with Apache Airflow and ensure reliability, observability, and alerts. • Develop and manage our data warehouse in Snowflake including modeling, performance tuning, security and governance. • Define and maintain data quality, lineage, catalog, and documentation practices. • Establish and track key metrics around data availability, latency, reliability, cost, and processing throughput. • Champion data engineering best practices: version control, CI/CD, automated testing, monitoring, and cost-efficient cloud usage. Key Responsibilities • Architect and lead implementation of a scalable cloud data platform built on Snowflake for analytics, reporting and advanced use cases. • Build robust ingestion pipelines using CDC techniques to capture changes from transactional systems into the data warehouse or lake. • Develop and maintain orchestration workflows in Airflow: schedule management, complex DAGs, dependency handling, back-fills, recoverability, alerting. • Implement data modelling (star/snowflake schemas, data vault, dimensional modelling) aligned with business domains and evolving requirements. • Manage data pipeline lifecycles: ingestion → transformation → storage → serving, ensuring SLAs for latency, throughput, and reliability.. • Collaborate cross-functionally with analytics, BI, data science, operations, product and business units to deliver data products. • Establish and enforce data governance, security and privacy controls: role-based access, masking, encryption, audit logging. • Monitor platform health: pipeline failures, resource usage, cost, data quality issues; respond and remediate proactively. • Stay abreast of new data technologies and drive continuous improvement in tooling, architecture, and processes. Required Qualifications • 8 + years of experience in data engineering, with at least 2-3 years in a senior or lead capacity architecture decisions). • Strong hands-on experience with Snowflake — schema design, performance optimisation, security. • Proven experience implementing and managing CDC (change-data-capture) ingestion pipelines from transactional systems. • Proven experience using Airflow to build and maintain complex data workflows. • Strong programming skills (Python, SQL, or Scala/Java) and proficiency with data processing frameworks. • Deep understanding of data modelling (relational, dimensional, data vault) and ETL/ELT design patterns. • Experience working in cloud environments (AWS, Azure or GCP) and managing cost-effective data infrastructure. • Excellent communication skills: able to interact with both technical and non-technical stakeholders, translate business requirements into technical solutions. • Excellent leadership skills: mentoring, setting standards, building high-performing teams, driving accountability and results.