Senior Manager, Platform Product

Quest Diagnostics is seeking a Senior Manager, Platform Product to lead the strategy and development of its Healthcare Analytics Solutions data platform. The role is responsible for technical roadmaps, data architecture, API-first design, data governance, streaming pipelines, observability, semantic data layers, GenAI readiness, and platform compliance.

Responsibilities:

• Partner with HAS business units, Data Engineering, and Quest IT to define, architect, and manage the data platform strategy, data contracts, and technical roadmap
• Drive detailed technical requirements for data architecture, dimensional/relational data modeling, and automated integration pipelines (ETL/ELT and streaming) to support the HAS product portfolio
• Establish and monitor platform performance metrics, including SLAs, SLOs, and SLIs for data freshness, pipeline latency, and platform uptime
• Serve as the primary technical liaison between business needs and IT engineering, translating complex business objectives into rigorous technical specifications, API definitions, and database schemas
• Define and enforce Data Contracts guarantee schema stability and prevent upstream changes from disrupting downstream products
• Drive specifications for automated, low-latency ingestion pipelines, evaluating performance and partition strategies across both batch processes and real-time streaming architectures (e.g., Apache Kafka, AWS Kinesis)
• Design and implement automated Data Observability frameworks (e.g., using Great Expectations, Monte Carlo, or Soda) to monitor data quality, schema drift, and lineage in production
• Perform hands-on data profiling, complex SQL querying, query optimization, and exploratory data analysis (EDA) to validate platform datasets and troubleshoot integration issues
• Be familiar with and able to review technical requirements, schema designs, and data models for a semantic information layer, optimized for agentic workflows, vector databases, and knowledge graphs (RAG pipelines)
• Collaborate with Advanced Analytics and Architecture teams to design the HAS semantic data layer to reduce dependency risks for complex product integrations
• Partner with Business Product teams and Data Scientists to incorporate complex semi-structured and unstructured healthcare data types (e.g., EMR notes, pathology reports, molecular diagnostics)
• Partner with engineering and data teams to define, standardize, and promote automated CI/CD and DataOps/MLOps processes that accelerate and secure the data product lifecycle
• Ensure platform compliance with HIPAA, PHI handling, and data privacy security controls through robust column-level encryption, masking, role-based access control (RBAC), and automated access governance

Requirements:

• • 5+ years of technical product management experience in data platforms, data engineering, or advanced analytics technology
• • 3+ years of hands-on experience as a Data Analyst, Data Engineer, or in a highly technical role directly writing queries, modeling data, and testing pipelines
• • Proven experience managing platform products through the software development lifecycle, including writing technical specifications, system architecture design, API definitions, and agile backlog management
• • Cloud & Data Warehousing: Deep expertise with cloud-based data platforms (AWS, GCP) and modern enterprise data warehousing/lakehouses (Snowflake, BigQuery, Databricks), including knowledge of cluster tuning and cost controls
• • Streaming & Message Queuing: Familiarity with event-driven architectures, streaming platforms (Apache Kafka, Flink), and schema registries
• • Data Engineering & Ops: Strong understanding of distributed computing, CI/CD pipelines, automated testing of data pipelines, and DataOps/MLOps concepts
• • AI & Graph Tech: Conceptual and practical understanding of Vector Databases (Pinecone, pgvector), Graph Databases (Neo4j), Knowledge Graphs, and LLM orchestration frameworks (e.g., LangChain, LlamaIndex) for semantic search and RAG
• • Product Tooling: Deep familiarity with technical product management tools (Jira, Confluence, Git, GitHub)
• • Advanced SQL Proficiency: Mastery of complex SQL queries (window functions, CTEs, query optimization) for independent data profiling, troubleshooting, and ad-hoc analysis
• • Programming/Scripting: Proficiency in Python or Scala for basic scripting, data manipulation (Pandas, PySpark), and REST API interaction
• • Schema Definition: Ability to write, read, and version schema definition files (Avro, JSON Schema, Protobuf)
• • Technical Translation: Proven ability to translate complex engineering constraints, database schemas, and architectural bottlenecks to business teams and vice-versa
• Bachelor's degree in Computer Science, Data Engineering, Information Systems, Mathematics, or related highly technical field
• • Deep experience with healthcare data standards and interoperability protocols (HL7 v2/v3, FHIR, DICOM)
• • Experience building or managing decentralized data architectures (Data Mesh) and defining data products
• • Strong working knowledge of modern data stack orchestration and transformation tools (e.g., dbt, Apache Airflow, Prefect)
• • Experience with Infrastructure as Code (IaC) principles (e.g., Terraform) and cloud financial management (FinOps) for data warehousing cost optimization
• • Demonstrated experience presenting complex engineering blueprints and system designs to senior leadership and non-technical stakeholders