Director, Data and Platform

RxSense

. Own the end-to-end data architecture, from ingestion through ETL, transformation, extracts, and stakeholder dashboards .

Posted 9/23/2026full-timeRemote • United StatesLead💰 $220,000 - $260,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in end-to-end data architecture, including ingestion, ETL, and transformation, while leading and mentoring a data and platform team. Proficient in building and deploying production-grade systems with a strong focus on DevOps practices and platform reliability.

Highest-signal resume keywords

Data ArchitectureDevOps ExperienceBig Data ProcessingTeam LeadershipProduction Code Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

ETLData TransformationData WarehousingNoSQLDistributed ProcessingProduction Code ShippingPHI/PII HandlingGitOps WorkflowsKubernetesCloud Infrastructure

Soft Skills

CommunicationCollaborationMentoring

Tools & Technologies

SparkKafkaMongoDBDynamoDBSnowflakeRedshiftBigQueryPostgresMySQLAWS

Industry Keywords

AI EngineeringData StrategyPlatform ArchitectureRegulated Data EnvironmentsGreenfield Platforms

Tech Stack

Tools & technologies

Amazon RedshiftAWSBigQueryCloudDynamoDBETLKafkaKubernetesMongoDBMySQLNoSQLPostgresSpark

About the role

Key responsibilities & impact

Own the end-to-end data architecture, from ingestion through ETL, transformation, extracts, and stakeholder dashboards
Own DevOps and infrastructure for the AI engineering team, including platform architecture from ingestion through serving
Set technical direction and standards for data infrastructure, pipelines, ETL/transformation logic, and platform reliability
Design accurate, timely, and trusted extract and reporting layers
Build, deploy, observe, and stabilize production-grade systems and infrastructure
Write and ship production code
Build and lead the data and platform team, including hiring and day-to-day direction
Mentor engineers on architecture, data design, DevOps, and platform thinking
Communicate technical tradeoffs to engineers, architects, and leadership
Partner with AI engineering leadership to align platform investments with product and research priorities
Translate business and executive priorities into data strategy and architecture decisions

Requirements

What you’ll need

8+ years architecting and building platforms in production (strong candidates with less experience can still be considered)
Proven, hands-on experience owning data architecture end to end, including ingestion, ETL and transformation, extracts, and the reporting or BI layer
Proven, hands-on DevOps experience building, deploying, and operating systems and infrastructure at scale
Track record of writing and shipping production code
Hands-on experience with big data/distributed processing such as Spark and Kafka
Experience with NoSQL and document stores such as MongoDB and DynamoDB
Experience with data warehousing such as Snowflake, Redshift, and BigQuery
Experience with high-throughput transactional databases including Postgres and MySQL
Rigorous PHI/PII handling and detection practices
Experience with GitOps workflows, Kubernetes, and cloud infrastructure such as AWS or equivalent
Excellent communication and collaboration skills
Experience mentoring engineers on architecture, data design, DevOps, and/or platform thinking
Prior experience building and leading a team, or clear readiness to take on direct reports
Comfort working in a small, fast-moving team where multiple hats are required
Bonus: experience architecting data platforms for AI/ML workloads, vector databases, regulated data environments, and greenfield platforms