Senior Data Platform Engineer - Remote in US

Jobgether SRL; United States; Remote; USD 160,000 - 170,000; Full time

Benefits offered by this job

Fully remote US

Healthcare data projects

Inclusive environment

Disability accommodations

Job summary

Jobgether SRL partners with a U.S.-based company to hire a Senior Data Engineer for a Data Platform. You will own data systems end to end, from ingestion to delivery, in a high-impact healthcare data environment.

You'll design robust ingestion, define data contracts, evolve schemas, and improve reliability. Collaboration across Engineering, Product, Operations, and Analytics is key, with a focus on performance, cost, and data quality.

Qualifications

• 5+ years of professional experience building and operating production data systems.
• Strong SQL and data modeling expertise, including grain, keys, historical data, dimensional modeling, and evaluating alternative data representations.
• Experience designing and operating batch and asynchronous data pipelines, with a solid understanding of distributed-system failure modes.
• Experience working with cloud-based data platforms, including knowledge of storage, query performance, scalability, and cost considerations.
• Strong understanding of data correctness, including validation, idempotency, late-arriving and duplicate records, schema evolution, backfills, and reprocessing.
• Working proficiency in Python for developing pipelines, services, tooling, and automated tests.
• Ability to make controlled, reversible changes to production systems while protecting downstream consumers.
• Strong analytical and problem-solving skills, with the ability to work effectively through ambiguous or incomplete requirements.
• Clear written and verbal communication skills, including the ability to explain technical decisions and tradeoffs to stakeholders outside engineering.
• Previous healthcare experience is not required, and candidates do not need experience with every technology used within the organization.
• Ability to work from the United States and authorization to work in the U.S. without employer-sponsored visa support.

Responsibilities

• Own production data systems and key data domains across the full lifecycle, from ingestion and validation through storage, transformation, and downstream delivery.
• Design robust ingestion patterns capable of handling incomplete, duplicated, delayed, malformed, and evolving data from external and internal sources.
• Define clear data contracts between source systems, ingestion processes, transformations, and downstream consumers.
• Design and maintain reliable data models with well-defined grain, keys, history, and business definitions to ensure consistent and trustworthy results.
• Safely evolve schemas, pipelines, and datasets while supporting retries, backfills, replay, and reprocessing without introducing corruption or duplication.
• Improve pipeline performance, observability, monitoring, and failure handling so issues can be detected, diagnosed, and resolved effectively.
• Partner with Engineering, Product, Operations, and Analytics teams to determine how data should be represented when requirements are incomplete, complex, or evolving.
• Make thoughtful architecture and production decisions that balance reliability, scalability, maintainability, performance, and cost.
• Document technical decisions and communicate data architecture, changes, and tradeoffs clearly to both technical and non-technical stakeholders.

Skills

SQL & Data Modeling

Data Pipelines

Python

Cloud Platforms

Data Quality

Schema Evolution

Batch Processing

Observability

Communication

Education

Bachelor’s degree

Job description

Jobgether SRL partners with a U.S.-based company to hire a Senior Data Engineer for a Data Platform. You will own data systems end to end, from ingestion to delivery, in a high-impact healthcare data environment.

You'll design robust ingestion, define data contracts, evolve schemas, and improve reliability. Collaboration across Engineering, Product, Operations, and Analytics is key, with a focus on performance, cost, and data quality.