Senior Technical Product Manager
New
S
Smile Digital HealthHealth Data Management
Remote USFull-TimeSenior
Salary120,000 - 145,000 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLSparkDatabricksDistributed Systems
Requirements
- 5+ years of Technical Product Management experience leading complex backend data platforms, distributed data engineering products, or big-data ingestion systems.
- Hands-on experience productizing solutions powered by Apache Spark (batch or streaming) and distributed data processing frameworks.
- Deep familiarity with Medallion Architecture (Bronze/Silver/Gold) and Delta Lake/Parquet performance patterns.
- Demonstrated experience optimizing complex, highly nested arrays and hierarchical data structures for analytical query engines.
- Direct experience productizing Master Data Management (MDM), entity resolution, or identity matching tools.
- Experience with event-driven architectures, Dead-Letter Queues (DLQs), and data replay/remediation workflows.
- Ability to comfortably write and execute SQL and Python to analyze raw datasets and define logic rules.
- Nice-to-have: Experience with healthcare data standards (HL7 FHIR, C-CDA, HL7 v2).
- Nice-to-have: Exposure to healthcare terminologies (SNOMED CT, LOINC, RxNorm, ICD-10).
- Nice-to-have: Familiarity with SQL-on-FHIR analytics standards.
Responsibilities
- Lead product vision and roadmap to transition data ingestion modules into scalable, standalone micro-services.
- Productize event-driven and streaming ingestion pipelines (Kafka, Spark) for high-velocity record processing.
- Define API contracts and integration specifications for HL7, C-CDA, and FHIR data sources.
- Develop analytics strategy using Databricks and Apache Spark, focusing on Medallion Architecture (Bronze/Silver/Gold).
- Define product requirements for FHIR-native MDM engines, including deterministic and probabilistic patient matching.
- Build end-to-end exception lifecycle management, including Dead-Letter Queues (DLQs) and idempotent replay mechanisms.
- Design interfaces for data stewards to manage record merges, unmerges, and data corrections.
View Full Description & ApplyYou'll be redirected to the employer's site
