Data Engineer - Senior
Why This Role Stands Out
Leverage your expertise in ETL and data quality to ensure the integrity of critical data pipelines within a reputable veteran-owned technology solutions company, with the flexibility of a hybrid work environment. You'll thrive in this role if you're passionate about building robust data systems and contributing to high-performing teams, so we encourage you to apply and explore this exciting opportunity.
Quick Overview
Job Description
HonorVet Technologies (SDVOSB) is a certified veteran-owned staffing and workforce solutions company recognized for its industry certifications, commitment to quality talent acquisition, and excellence in delivering IT, healthcare, federal, state, and SLED (State, Local, and Education) staffing services, helping organizations build reliable, compliant, and high-performing teams across mission-critical sectors.
Job Title: NCDPI - Data Engineer - Senior
Duration: 6 months
Location: 301 N. Wilmington St, Raleigh, NC( Hybrid )
Job Summary
We are seeking a skilled mid-level+ Data Engineer to join our team and focus on quality assurance, quality checking, and ETL processes. The successful candidate will be responsible for ensuring the integrity and accuracy of data transferred from a shared file transfer service to an S3 bucket and subsequently into and through our Snowflake data platform. This data will be utilized by downstream applications and reporting systems. These applications and the corresponding consumed data are critical to business process execution.
Key Responsibilities:
- Quality Assurance & Quality Checking: Implement and maintain data quality to ensure the accuracy and reliability of data throughout the ETL process.
- ETL Processes: Design, develop, and optimize ETL workflows to efficiently transfer data from file transfer services to S3 buckets and Snowflake.
- Data Integration: Ensure seamless data integration into data platform, enabling efficient consumption by downstream applications and reporting tools.
- Data Quality Management: Address data quality challenges, including inconsistencies in source data that do not meet ingestion requirements, which can lead to load failures or data backouts.
- Collaboration: Work closely with business owners, data analysts, business intelligence teams, and other stakeholders to understand data requirements and deliver high-quality data solutions.
- Monitoring & Troubleshooting: To preserve data flow and integrity, monitor pipelines, identify issues, and implement solutions.
Qualifications (Knowledge/Skills/Abilities):
- Demonstrated mid-level+ experience in data engineering, with a emphasis on data quality assurance and ETL processes.
- Expertise in Python, PyPI, and SQL
- Expert analytical and problem-solving skills.
- Demonstrate a strong understanding of cybersecurity principles related to code development, DevOps, data access, and fundamental cybersecurity.
- Understanding of fundamental public-cloud capabilities.
- Proven capacity to comprehend business needs and convert them into technical requirements.
- Demonstrated excellence in communication and collaboration abilities.
- Proven capacity to define success, deliver, and operate in an agile setting.
Skill | Required / Desired | Amount | of Experience |
Demonstrated mid-level+ experience in data engineering, with an emphasis on data quality assurance and ETL processes. | Required | 5 |
|
Expertise in Python, PyPI, and SQL | Required | 5 |
|
Demonstrate a strong understanding of cybersecurity principles related to code development, DevOps, data access, and fundamental cybersecurity. | Required | 5 |
|
Understanding of fundamental public-cloud capabilities. | Required | 5 |
|
Proven capacity to comprehend business needs and convert them into technical requirements. | Required | 5 |
|
Skills
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