- Esperienza
- 4–9 yrs
- Stipendio
- —
- Aperture
- 1
- Pubblicato
- 1 ora fa
- Work mode
- In ufficio
- Istruzione
- Any graduate
- Eligibility
- Applicants are eligible even if a graduation degree is not required.
- Resume
- Required to apply
Where you'll work
Descrizione del lavoro
About the Company
IntraEdge Technology is a global technology talent, services, and training organization that operates with the flexibility of a much smaller team while serving clients at scale. Founded in 2002 in Phoenix, AZ, the company supports innovation-focused businesses by helping them find the right talent, deliver adaptable professional services, and build skills through training. Its work spans sectors such as banking, finance, insurance, healthcare, and airlines, with projects for clients in the US and UK including American Express, JP Morgan, Facebook, Nike, UnitedHealthcare, Anthem, and Wells Fargo.
Role Overview
The organization is seeking an experienced Data Engineer to build and support scalable data platforms and pipelines. This role requires strong hands-on knowledge of Python, PySpark, AWS services such as Glue and Lambda, and Snowflake. The engineer will help create reliable data integration processes that support analytics and reporting needs across the business.
Key Responsibilities
The selected candidate will design, develop, and improve ETL/ELT pipelines using Python, PySpark, and AWS Glue. The role also involves bringing in data from both structured and unstructured sources, transforming it for downstream use, and integrating it into the wider data ecosystem.
In addition, the engineer will work deeply with Snowflake for data modeling, warehouse design, performance improvement, and query tuning. Automation of workflows and processing tasks through AWS Lambda and other AWS-native services will also be an important part of the job.
The position includes maintaining data quality, consistency, and security across systems, partnering with data scientists, analysts, and business stakeholders, and actively monitoring, debugging, and enhancing pipeline performance. Clear documentation of data flows, procedures, and best practices will also be expected.
Required Qualifications
Candidates should have 4-9 years of proven experience in data engineering or a closely related role. Strong coding ability in Python and practical experience with PySpark are essential.
Applicants must be familiar with AWS services including Glue, Lambda, S3, CloudWatch, and IAM, along with Snowflake concepts such as data modeling, warehouse design, and query optimization. A strong grasp of ETL/ELT, data warehousing, and large-scale data processing is required, as well as solid SQL knowledge and tuning skills.
Experience with Git, CI/CD pipelines, deployment practices, data governance, security, and compliance is expected. The role also calls for strong problem-solving ability, communication skills, and cross-functional collaboration.
Eligibility
Open to applicants without a graduation requirement.