Senior Data Engineer, Business OperationsSK Life Science, Inc. • Paramus, New Jersey, United States
Senior Data Engineer, Business Operations
SK Life Science, Inc.
- Paramus, New Jersey, United States
- Paramus, New Jersey, United States
Über
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-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.aligned data models that enable forecasting, planning, and optimization across the value chain, beginning with supply chain operations. This is a highimpact senior role for someone who thrives in owning a data ecosystem endtoend and building AIcentric data infrastructure from the ground up.
Responsibilities
Analyze existing databases and redesign them for AI/ML readiness, including ontologydriven and semantic data modeling. Architect and implement centralized Data Lake and scalable, robust data pipelines supporting operational workflows and AIdriven decision processes. Build and maintain highquality data transformations using dbt and enforce software engineering best practices across the data stack. Design featureready 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, experimentationdriven culture, balancing rapid PoC execution with longterm architectural integrity.
Qualifications
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 largescale distributed data processing, data manipulation, automation, and pipeline development.
Expertlevel 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. Handson 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.
Strongly Preferred
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 ontologybased 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), BizOps, RevOps, or Commercial Operations. Experience in regulated industries (e.g., biopharma, healthcare, finance). Experience in a BizOps or highly crossfunctional technical role. Handson experience with Snowflake architecture.
Who Thrives in This Role
Someone who enjoys owning a data ecosystem endtoend 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 fastpaced, startuplike environment where innovation and speed matter. An "Agile Operator" who can rapidly prototype for PoCs while architecting for longterm scalability and reliability.
Required
Preferred
Job Industries
Other
Sprachkenntnisse
- English
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