AWS Data Engineer

🕒 April 1

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Scalepex

51 - 200 employees

🤝 B2B

👥 HR Tech

🤖 Artificial Intelligence

B2B • HR Tech • Artificial Intelligence

Scalepex is a minority-owned company that specializes in talent solutions to help businesses scale and achieve their strategic goals. Leveraging a combination of creativity, strategy, and execution, Scalepex uses a unique AI platform to enhance the quality of talent, providing staffing and placement services to industries such as technology, finance, healthcare, and more. Their approach focuses on individualized support, cost management, and strategic consultation across areas like mergers and acquisitions, software development, data enablement, and more. With a strong emphasis on social responsibility, Scalepex aims to connect underserved communities with world-class opportunities, ensuring both client success and personal and professional satisfaction for their team members.

📋 Description

• 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. • Use AWS Step Functions to orchestrate workflows across data pipelines; experience with Airflow is acceptable but Step Functions is preferred. • Implement ETL/ELT processes using PySpark, Python, and Pandas to clean, transform, and integrate data from multiple sources into unified datasets. • Leverage experience with complex distributed systems to ensure reliability, scalability, and performance in handling large-scale utility data. • Use AWS Lambda functions to build serverless solutions for automating data processing tasks. • Design data models tailored for utilities use cases (e.g., energy consumption forecasting) to enable advanced analytics. • Continuously monitor and improve the performance of data pipelines to reduce latency, enhance throughput, and ensure high availability. • Implement robust security measures to protect sensitive utility data and ensure compliance with industry regulations.

🎯 Requirements

• 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. • Knowledge of data governance practices to ensure accuracy, consistency, and security of data. • Strong experience in AWS data engineering • Ability to work independently • Ability to work with a cross-functional teams, including interfacing and communicating with business stakeholders • Professional oral and written communication skills • Strong problem solving and troubleshooting skills with experience exercising mature judgement • Excellent teamwork and interpersonal skills • Ability to obtain and maintain the required clearance for this role

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