Scalepex
AWS Data Engineer - Fully Remote - US Only
Remote role where the employee must remain based in a particular country.
United States only
Employer listed it 21 months ago · Added today
Been open since 21 months ago. Long-running listings are sometimes left up after the role is filled.
Salary
Not stated
Location
United States only
Timezone
US East
Contract
Full-time
Experience
Mid
Category
Data
This employer didn't state pay. Jobs like this usually pay around $110k–$200k a year, a typical range taken from 226 mid-level data roles on Nomaders that do state pay. It's a guide, not an offer.
Remote flexibility
Work from home
This is a remote role, but the employee must be based in United States. It is work from home rather than work from anywhere.
What the employer says
- Source listing states candidate location: "Plano, United States"
What Nomaders makes of it
- Residency required in United States
- Payroll and tax are likely handled in that country only
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
❋ Why Scalepex?
Scalepex is a dynamic services firm specializing in providing solutions for premium brands like Nike, Pepsi, Toyota, Virgin and Walgreens. Our mission is to connect prominent market leaders with top-tier professionals from around the world, fostering collaboration, efficiency, and growth.
❋ Take your portfolio to the next level by working with one of our fastest growing clients.
Join the Innovation Frontier at Scalepex!
About the Role
We are seeking an experienced AWS Data Engineer with a strong background in building scalable data solutions and expertise in utilities-related datasets. The ideal candidate will have at least 5 years of experience in data engineering, a deep understanding of distributed systems, and proficiency with AWS services and tools like Step Functions, Lambda, Glue, and Redshift. This role will focus on designing, developing, and optimizing data pipelines to support analytics and decision-making in the utilities industry.
Key Responsibilities
Design and Build Data Pipelines : Develop scalable, reliable data pipelines using AWS services (e.g., Glue, S3, Redshift) to process and transform large datasets from utility systems like smart meters or energy grids.
Workflow Orchestration : Use AWS Step Functions to orchestrate workflows across data pipelines; experience with Airflow is acceptable but Step Functions is preferred.
Data Integration and Transformation : Implement ETL/ELT processes using PySpark, Python, and Pandas to clean, transform, and integrate data from multiple sources into unified datasets.
Distributed Systems Expertise : Leverage experience with complex distributed systems to ensure reliability, scalability, and performance in handling large-scale utility data.
Serverless Application Development : Use AWS Lambda functions to build serverless solutions for automating data processing tasks.
Data Modeling for Analytics : Design data models tailored for utilities use cases (e.g., energy consumption forecasting) to enable advanced analytics
Optimize Data Pipelines : Continuously monitor and improve the performance of data pipelines to reduce latency, enhance throughput, and ensure high availability.
Ensure Data Security and Compliance : Implement robust security measures to protect sensitive utility data and ensure compliance with industry regulations.
Requirements
Required Qualifications
Minimum of 5 years of experience in data engineering
Proficiency in AWS services such as Step Functions, Lambda, Glue, S3, DynamoDB, and Redshift.
Strong programming skills in Python with experience using PySpark and Pandas for large-scale data processing.
Hands-on experience with distributed systems and scalable architectures.
Knowledge of ETL/ELT processes for integrating diverse datasets into centralized systems.
Familiarity with utilities-specific datasets (e.g., smart meters, energy grids) is highly desirable.
Strong analytical skills with the ability to work on unstructured datasets.
Requirements
- ·Required Qualifications
- ·Minimum of 5 years of experience in data engineering
- ·Proficiency in AWS services such as Step Functions, Lambda, Glue, S3, DynamoDB, and Redshift.
- ·Strong programming skills in Python with experience using PySpark and Pandas for large-scale data processing.
- ·Hands-on experience with distributed systems and scalable architectures.
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, work from home, matches where you plan to live and work.
- 2Tailor your CV to the role at Scalepex, mentioning your remote working experience and working hours (US East).
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 19h ago. Last checked 23 Sept. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
Similar roles
Other open data roles with comparable remote rules.
Free to apply, no account needed.
Typically $110k to $200k per year · You'll be taken to the employer's careers page.