Junior PySpark Engineer – AWS/EMR
Salário Estimado
R$ 10.417,00 - R$ 12.500,00
Tecnologias
Regular
Score da Vaga
Descrição da Vaga
Location: Remote (EST Time Zone Preferred) - 5 Days a month in the Office Duration: 6 Months Contract About Big Rio: Big Rio is a remote-based, technology consulting firm with headquarters in Boston, MA.
We deliver software solutions ranging from custom development and software implementation to data analytics and machine learning/AI integrations.
As a one-stop shop, we attract clients from a variety of industries due to our proven ability to deliver cutting‑edge, cost‑effective software solutions.
Job Overview: We are seeking a Junior PySpark Engineer with strong hands‑on experience in building distributed data pipelines using Apache Spark on AWS EMR .
The ideal candidate is proficient in Python , has worked with Databricks , and has a solid understanding of GxP‑compliant environments.
This is a coding‑heavy role – not Dev Ops or AWS administration – where you’ll contribute directly to the architecture and development of robust data solutions in a highly regulated, cloud‑native environment.
Key Responsibilities:
We prohibit discrimination and harassment of any kind based on race, religion, national origin, sex, sexual orientation, gender identity, age, pregnancy, status as a qualified individual with disability, protected veteran status, or other protected characteristic as outlined by federal, state, or local laws.
Big Rio makes hiring decisions based solely on qualifications, merit, and business needs at the time.
All qualified applicants will receive equal consideration for employment.
Big Rio is a leading AI, Gen AI, Data and Analytics professional services company.
We are focused on Healthcare, Pharma, Digital Health, Provider, and Payer Industry segments with several innovative solutions. #J-18808-Ljbffr
Requisitos
- We are seeking a Junior PySpark Engineer with strong hands‑on experience in building distributed data pipelines using Apache Spark on AWS EMR
- The ideal candidate is proficient in Python
- , has worked with Databricks
- , and has a solid understanding of GxP‑compliant environments
- 2–4 years of experience in software or data engineering with a focus on distributed systems
- Deep hands‑on experience with Apache Spark
- , Py Spark , and AWS (especially EMR)
- Strong programming skills in Python
- Solid understanding of cloud‑native architectures
- Familiarity with GxP compliance and working in regulated data environments
- Proven ability to independently design and develop data pipelines (not a Dev Ops/AWS admin role)
- Experience with distributed computing and high-volume ETL pipelines
Responsabilidades
- This is a coding‑heavy role – not Dev Ops or AWS administration – where you’ll contribute directly to the architecture and development of robust data solutions in a highly regulated, cloud‑native environment
- Design, develop, and maintain distributed ETL data pipelines using PySpark on AWS EMR
- Work within a GxP‑compliant environment, ensuring data integrity and regulatory alignment
- Write clean, scalable, and efficient PySpark code for large-scale data processing
- Utilize AWS cloud services for pipeline orchestration, compute, and storage
- Collaborate closely with cross‑functional teams to deliver end‑to‑end data solutions
- Participate in code reviews, testing, and deployment of pipeline components
- Ensure performance optimization, fault tolerance, and scalability of data workflows
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