Senior Data Engineer

Appnovation Technologies•New York, NY

3h•Hybrid

About The Position

Join forces with Appnovation to deliver high-impact results for one of our key strategic partners - a global leader in their field. This engagement offers a unique vantage point into a world-class organization with exceptional opportunities for professional growth and long-term career advancement As a Senior Data Engineer, you will manage the "discovery-to-scale" pipeline, identifying recurring patterns in the field and handing off validated solutions to Platform Engineers for enterprise generalization. In this forward-deployed role, you will bridge the gap between building technical products and solving real-world business problems through rapid solution delivery and deep domain immersion. Your primary objective is to design and build data integration, storage systems, and infrastructure that enable analytics and AI capabilities. This role requires high-level autonomy, where you will define your own direction within strategic goals, influence multiple teams, and navigate high complexity and ambiguity to deliver tangible business results.

Requirements

Bachelor's degree in Computer Science or Engineering with 8–12 years of relevant experience leading and delivering complex data engineering projects with multi-team or business impact.
Proven expertise in designing, building, and maintaining robust, scalable data pipelines (ETL/ELT). Must demonstrate the ability to navigate complex enterprise data landscapes, effectively handle undocumented schemas, and implement resilient integration solutions for high-volume data.
Deep expertise in deploying and managing data infrastructure on cloud platforms (AWS, Azure, or GCP). Proficient in Infrastructure as Code (Terraform/CloudFormation) and establishing end-to-end CI/CD pipelines for data solutions.
Strong skills in conceptual, logical, and physical data modeling, with the ability to balance data normalization, query performance, and safely manage complex schema migrations in production.
Mastery of incorporating AI tools to optimize data engineering workflows and the ability to design data validation and evaluation frameworks that support the deployment and governance of AI/ML models.
Capability to rapidly prototype and build complete, end-to-end data applications across diverse technology stacks, prioritizing solution speed and business value while effectively managing technical debt.
Direct experience defining and monitoring service level objectives (SLOs/SLIs). A track record of designing highly resilient data systems that ensure graceful degradation and driving post-incident improvements.
Ability to make sound architectural trade-offs, design scalable system components, and produce high-quality, well-tested code that adheres to enterprise standards.
Polymath Oriented: You bridge gaps between engineering, design, business, and science, rapidly immersing yourself in new domains to speak the language of the business.
Curious Explorer: You seek out ambiguity rather than avoiding it, driving team curiosity through challenging questions and creating an environment that encourages experimentation.
Outcome Owner: You drive an accountability culture focused on business impact rather than just deliverables, owning relationships and making trade-offs between custom solutions and generalizable work.
Systems Thinker: You map complex system interactions across technical and business domains, anticipating cascading effects and understanding how technology changes impact operations.
Precise Communicator: You translate seamlessly between technical and business language, ensuring requirements are clear enough to enable AI generation and facilitate productive discussions with stakeholders.
Problem Discoverer: You embed with users to discover latent needs, turning ambiguity into clear problem statements rather than waiting for defined tasks.