Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

Drive the next generation of our high-throughput, enterprise data ingestion and data management architecture. Lead the strategic transformation of our Data Ingress Engine using technologies like Apache Spark, Databricks, and Medallion Lakehouse Architecture. Own the product roadmap for our core Master Data Management (MDM) and Data Remediation Engines, defining how millions of disparate clinical records are cleansed, matched into a single "Golden Patient Record," and safely reprocessed when errors occur. Thrive at the intersection of distributed systems, high-volume streaming/batch data pipelines, and complex data models.

Responsibilities

Lead the product vision and roadmap to decouple core data ingestion modules from operational API boundaries, turning them into highly scalable, standalone micro-services.
Productize event-driven and streaming ingestion pipelines (e.g., Kafka/Spark Structured Streaming) capable of processing billions of high-velocity records.
Establish clear API contracts, event interfaces, and integration specs for external sources feeding raw payloads (HL7 v2, C-CDA, FHIR JSON, Claims) into our platform.
Define requirements for transitioning mass analytics pipelines onto a Databricks / Medallion Architecture using Apache Spark.
Drive the design of optimized Silver and Gold layer datasets, ensuring deeply nested JSON formats (e.g., FHIR) are efficiently flattened and structured into high-performance columnar models (Delta Lake/Parquet) for OLAP analytics.
Partner with engineering architects to balance real-time, low-latency micro-batches against cost-optimized, high-throughput daily batch workloads.
Own the product requirements for our FHIR-native MDM Engine, defining rules for deterministic and probabilistic patient matching at scale.
Productize Survivorship Logic to establish rules for creating and maintaining the "Golden Record" across fragmented data feeds.
Design crosswalk management capabilities to track source-to-target entity linkages across millions of patient lives.
Build out the end-to-end exception lifecycle for data validation failures—from isolation in Dead-Letter Queues (DLQs) to structured error reporting.
Define requirements for Data Steward interfaces and APIs, allowing users to review validation exceptions, perform manual record merges/unmerges, and correct bad data payloads.
Architect Idempotent Replay Mechanisms to re-ingest corrected payloads through Spark processing pipelines without generating duplicate data or corrupting state.

Requirements

5+ years of Technical Product Management experience leading complex backend data platforms, distributed data engineering products, or big-data ingestion systems.
Proven track record 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, validate engine output, and define logic rules.
Experience with healthcare data standards, including HL7 FHIR, C-CDA, or HL7 v2.
Exposure to healthcare terminologies (SNOMED CT, LOINC, RxNorm, ICD-10).
Familiarity with SQL-on-FHIR analytics standards.

Skills

Apache Spark
Databricks
Medallion Lakehouse Architecture
Kafka
Spark Structured Streaming
HL7 v2
C-CDA
FHIR JSON
Delta Lake
Parquet
Master Data Management (MDM)
SQL
Python

Location

Remote

Work Type

Remote

Experience Level

Senior

Salary/Compensations

$120,000 - $145,000

Benefits

Remote Work Environment
Flexible Time Away From Work Policy including PTO, Personal and Sick Days
Competitive Salary and Health/Medical Benefits
RRSP/TFSA/401K Employee Contribution
Life and Disability
Employee Assistance Program
FHIR Study Program and Skillsoft Learning
Super HAPI Fun Club

About the Company

Smile Digital Health supports a mandate for #BetterGlobalHealth through its innovative health data platform and data management solutions, used in over 20 countries.
The company was #19 on Deloitte's Technology Fast 50 Ranking for 2024.
Smile Digital Health makes it easy for healthcare stakeholders to collect and exchange data with its leading FHIR-based data liberation platform.
The Smile platform enables people and organizations to better manage healthcare data, generating and liberating structured healthcare data for effective delivery across care teams and health systems.
Smile's core values include respect, inclusion, embracing our differences, and celebrating shared values.
The company is dedicated to fostering a workplace that values diversity, equity, and inclusion.
Smile welcomes and encourages candidates of all backgrounds to apply.

Equal Opportunity

Smile discloses that artificial intelligence (AI) may be used in portions of the recruitment and selection process, such as resume screening or application assessment. All hiring decisions are ultimately made by qualified human decision-makers, and AI tools are used to support — not replace — fair and equitable hiring practices.
We welcome and encourage candidates of all backgrounds to apply.
Candidates are encouraged to inform us if they wish to discuss or require accommodations during interviews or while working at Smile.