Senior Data Engineer, Business Operations

Job Location:

US-NJ-Paramus

The Senior Data Engineer, Biz Ops will play a critical role in architecting the data infrastructure powering our AI-driven business operations platform. This role is responsible for analyzing the current database environment, redesigning it for AI-native use cases, and establishing the foundational data architecture for our end-to-end decision-intelligence platform-driven business operations platform. You will design scalable data ecosystems—including Data Lakes, Data Pipelines, and semantic modeling layers—using modern engineering standards (dbt, orchestration frameworks, CI/CD).

Working closely with commercial and business operations experts, you will dissect existing workflows and reimagine them as AI-ready, streamlined processes in collaboration with AI Scientists and AI Engineers. You will translate ambiguous operational and business challenges into clean, reliable, ontology-aligned data models that enable forecasting, planning, and optimization across the value chain, beginning with supply chain operations. This is a high-impact senior role for someone who thrives in owning a data ecosystem end-to-end and building AI-centric data infrastructure from the ground up.

• Analyze existing databases and redesign them for AI/ML readiness, including ontology-driven and semantic data modeling.
• Architect and implement centralized Data Lake and scalable, robust data pipelines supporting operational workflows and AI-driven decision processes.
• Build and maintain high-quality data transformations using dbt and enforce software engineering best practices across the data stack.
• Design feature-ready data models to support AI/ML use cases such as forecasting, classification, and optimization.
• Develop secure and reliable data ingestion frameworks (batch and streaming) with strong observability and performance controls.
• Partner with Commercial, Marketing, and AI teams to translate business problems into data requirements, semantic models, and scalable pipelines.
• Implement data quality, lineage, and governance practices aligned with enterprise standards.
• Lead technical direction on modern data stack architecture and continuously improve scalability, efficiency, and maintainability.
• Contribute to an agile, experimentation-driven culture, balancing rapid PoC execution with long-term architectural integrity.

• Education
  :
  Bachelor's degree or higher in Computer Science, Engineering, or related field.
• Experience
  : 5+ years of hands-on experience in Data Engineering or technical Analytics Engineering, with deep experience building data lakes and orchestrating complex pipelines.
• Skills
  :
  • Strong programming proficiency in Python and PySpark for large scale distributed data processing, data manipulation, automation, and pipeline development.
• Expert-level SQL for data modeling, complex transformations, and performance optimization.
• Experience with modern data lake table formats such as Apache Iceberg.
• Familiarity with Medallion Data Architecture (Bronze/Silver/Gold) for scalable and governed data processing.
• Hands-on experience with modern transformation frameworks (e.g., dbt) and orchestration tools (e.g., Airflow or Python-based schedulers).
• Knowledge of core AWS or Azure data services and data observability practices.
• Experience optimizing data models for BI and visualization tools (e.g., Tableau).
• Ability to define business metrics and derive semantic meaning from operational KPIs.

• Master's degree or higher in a quantitative or technical field.
• Experience working with ML pipelines (e.g., MLflow, Feature Stores) and collaborating with AI Scientists/Engineers.
• Knowledge of ontology-based modeling, semantic layers, and modern data architectures (e.g., Data Mesh, Data Fabric).
• Experience with Graph Databases (e.g., Neo4j) for semantic modeling, ontology alignment, or operational knowledge graphs.
• Domain experience in Supply Chain Management (SCM), Biz Ops, Rev Ops, or Commercial Operations.
• Experience in regulated industries (e.g., biopharma, healthcare, finance).
• Experience in a Biz Ops or highly cross-functional technical role.
• Hands-on experience with Snowflake architecture.

• Someone who enjoys owning a data ecosystem end-to-end and building from zero to one.
• A strategic thinker who balances strong technical depth with understanding of real business context.
• An engineer who thrives in close collaboration with Commercial and AI teams to define how data powers decisions.
• A builder comfortable operating in a fast-paced, start-up like environment where innovation and speed matter.
• An "Agile Operator" who can rapidly prototype for PoCs while architecting for long-term scalability and reliability.