Engagement Type
Contract
Short Description
Typical Experience: 60-84 months
Complete Description
***The manager would like the candidate to be onsite regularly throughout the position. The amount of onsite time per week will be negotiable. However, weekly onsite time will be required.
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 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.
Required/Desired Skills
| Skill | Required/Desired | Amount | of Experience |
| Demonstrated mid-level+ experience in data engineering, with an emphasis on data quality assurance and ETL processes. | Required | 5.0 | Years |
| Expertise in Python, PyPI, and SQL | Required | 5.0 | Years |
| Demonstrate a strong understanding of cybersecurity principles related to code development, DevOps, data access, and fundamental cybersecurity. | Required | 5.0 | Years |
| Understanding of fundamental public-cloud capabilities. | Required | 5.0 | Years |
| Proven capacity to comprehend business needs and convert them into technical requirements. | Required | 5.0 | Years |
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