UST
Website:
ussmokeless.com
Company:
https://www.linkedin.com/company/ustglobal
Seniority: Not Applicable
Industries: IT Services and IT Consulting
Job details:
Role Description
Who we are:
At UST, we help the world’s best organizations grow and succeed through transformation. Bringing together the right talent, tools, and ideas, we work with our client to co-create lasting change. Together, with over 30,000 employees in 30+ countries, we build for boundless impact—touching billions of lives in the process. Visit us at .
Summary:
Job Summary
We are seeking a skilled and motivated Big Data Engineer with 2-4 years of experience in designing, developing, and maintaining large-scale data processing systems. The ideal candidate should have strong expertise in AWS cloud services, Python, and PySpark, along with hands-on experience in building scalable data pipelines, data lakes, and ETL solutions. The candidate will work closely with data architects, analysts, and business stakeholders to deliver high-quality data solutions that support analytics and business intelligence initiatives.
Key Responsibilities
- Design, develop, and maintain scalable and reliable data pipelines for processing large volumes of structured and unstructured data.
- Build and optimize ETL/ELT workflows using PySpark and Python.
- Develop and manage data lake and data warehouse solutions on AWS Cloud.
- Implement data ingestion frameworks from multiple data sources, including databases, APIs, files, and streaming platforms.
- Leverage AWS services such as S3, Glue, EMR, Lambda, Redshift, Athena, CloudWatch, and IAM for data engineering solutions.
- Perform data transformation, cleansing, validation, and enrichment to ensure high data quality.
- Optimize Spark applications for performance, scalability, and cost efficiency.
- Collaborate with data scientists, analysts, and business teams to understand data requirements and deliver solutions.
- Monitor data pipelines and resolve production issues to ensure data availability and reliability.
- Implement security best practices, governance, and compliance standards across data platforms.
- Participate in code reviews, unit testing, and deployment activities.
- Create technical documentation and maintain operational runbooks.
Required Skills
Technical Skills
- Strong experience in Python programming.
- Hands-on expertise in PySpark and distributed data processing.
- Experience working with AWS Cloud Platform.
- Knowledge of AWS services including:
- Amazon S3
- AWS Glue
- Amazon EMR
- AWS Lambda
- Amazon Redshift
- Amazon Athena
- AWS IAM
- CloudWatch
- Good understanding of ETL/ELT concepts and data pipeline development.
- Experience with SQL and relational databases.
- Knowledge of Data Warehousing concepts and dimensional modeling.
- Familiarity with version control tools such as Git.
Skills
AWS, Data Engineering, PySpark
Skills
AWS, Data Engineering, PySpark
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