Member of Technical Staff (Data Engineering)

Solstice•New York, NY

1d•$200,000 - $300,000

About The Position

Solstice is redefining how life sciences organizations commercialize their therapeutics by building a commercial engine that allows pharmaceutical marketers to launch campaigns at 100x the speed. This role is for the first data engineer to build the data foundation for Solstice's media activation and measurement products. The long-term goal is to close the loop between the content created, the audiences who see it, and the outcomes it drives, then use that evidence to make the next campaign better. This requires reliable data across systems that were not designed to work together, handling various data formats, reconciling identifiers, and managing data that is late, changes shape, contains duplicates, or includes off-list/unmatched records. The engineer will own the end-to-end foundation, including the cloud warehouse, ingestion and transformation pipelines, identity and attribution mappings, data quality, observability, and interfaces for product, media, and AI teams. This is a production systems role, not a reporting or dashboard-only position.

Requirements

Strong Python and SQL, with experience building and operating production data systems.
Deep experience with ETL or ELT pipelines, data modeling, workflow orchestration, and a modern cloud warehouse or lakehouse.
Experience ingesting messy third-party data and reconciling records across systems with inconsistent identifiers and schemas.
Strong instincts for data correctness: validation, lineage, observability, backfills, deduplication, and failure recovery.
Experience designing systems that are reliable under growing volume, changing partner contracts, and imperfect upstream inputs.
Independent judgment and end-to-end ownership. You can turn an ambiguous business goal into a technical plan, ship it, and operate it.
Clear communication. You can explain data quality and measurement tradeoffs to technical and non-technical partners, and you are comfortable working directly with external vendors.
A high bar for craft, urgency, and follow-through.

Nice To Haves

Experience with GCP and BigQuery, or comparable depth with AWS, Azure, Snowflake, Databricks, or Redshift.
Experience with data transformation and orchestration tools such as dbt, Airflow, Dagster, or Prefect.
Experience in adtech, media delivery, measurement, attribution, or marketing data platforms.
Familiarity with healthcare or life sciences data, including NPI-keyed HCP data, claims, or prescription signals.
Experience building secure data systems for regulated, privacy-sensitive, or enterprise environments.
Experience preparing high-quality data for experimentation, analytics, machine learning, or AI systems.
Experience integrating with DSPs, endemic publishers, identity vendors, or claims-data providers.
Familiarity with creative-level or component-level measurement, incrementality, or experiment design.
Experience building a data platform from zero to one at an early-stage company.

Responsibilities

Design, build, and operate the cloud data platform for Solstice's media products, from raw partner data through trusted, analysis-ready models.
Ingest daily event and delivery logs from DSPs, publishers, claims-data providers, client systems, and Solstice's own content platform.
Build durable mappings across vendor identifiers, NPIs, campaigns, audiences, assets, and atomic creative elements.
Handle the hard cases in third-party data: de-aggregation, off-list records, unmatched identities, duplicates, late-arriving data, schema drift, and backfills.
Create canonical data models that connect creative attributes and exposures to clicks, engagement, and longer-lag outcomes such as prescription or claims signals.
Build reliable batch and event-driven pipelines with clear lineage, idempotent processing, automated data-quality checks, and actionable alerting.
Make partner integrations repeatable, including APIs, secure file transfer, validation, reconciliation, and audit trails.
Provide clean datasets and services that support campaign measurement, experimentation, attribution, and the creative-to-performance feedback loop.
Own the reliability, security, and cost of the data platform as volume and the number of partners grow.
Work directly with media, product, AI, and customer teams to launch the first campaigns, investigate discrepancies, and turn real operating problems into durable platform capabilities.