Duration: 12 months Contract with possibility to extension
Work Type: Onsite
The manager requires the candidate to be onsite regularly throughout the position.
The amount of onsite time per week is negotiable but weekly onsite attendance is mandatory.
Job Summary Data Engineer
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 ensure 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 which 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 the 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: Monitor pipelines identify issues and implement solutions to preserve data flow and integrity.
Qualifications (Knowledge/Skills/Abilities)
Demonstrated mid-level experience in data engineering with an emphasis on data quality assurance and ETL processes.
Expertise in Python PyPI and SQL
Expert analytical and problem-solving skills
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
Experience Requirements
Skill
Requirement
Years
Mid-level experience in data engineering with emphasis on data quality assurance and ETL processes
Required
5 Years
Expertise in Python PyPI and SQL
Required
5 Years
Strong understanding of cybersecurity principles related to code development DevOps data access and fundamental cybersecurity
Required
5 Years
Understanding of fundamental public-cloud capabilities
Required
5 Years
Ability to comprehend business needs and convert them into technical requirements
Required
5 Years
Job Title: Senior Data Engineer Location: 301 N. Wilmington St. Raleigh NC Duration: 12 months Contract with possibility to extension Work Type: Onsite The manager requires the candidate to be onsite regularly throughout the position. The amount of onsite time per week is negotiable but weekly ons...
Job Title: Senior Data Engineer
Location: 301 N. Wilmington St. Raleigh NC
Duration: 12 months Contract with possibility to extension
Work Type: Onsite
The manager requires the candidate to be onsite regularly throughout the position.
The amount of onsite time per week is negotiable but weekly onsite attendance is mandatory.
Job Summary Data Engineer
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 ensure 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 which 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 the 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: Monitor pipelines identify issues and implement solutions to preserve data flow and integrity.
Qualifications (Knowledge/Skills/Abilities)
Demonstrated mid-level experience in data engineering with an emphasis on data quality assurance and ETL processes.
Expertise in Python PyPI and SQL
Expert analytical and problem-solving skills
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
Experience Requirements
Skill
Requirement
Years
Mid-level experience in data engineering with emphasis on data quality assurance and ETL processes
Required
5 Years
Expertise in Python PyPI and SQL
Required
5 Years
Strong understanding of cybersecurity principles related to code development DevOps data access and fundamental cybersecurity
Required
5 Years
Understanding of fundamental public-cloud capabilities
Required
5 Years
Ability to comprehend business needs and convert them into technical requirements