Data Engineer 3
3 weeks ago
LOCATION: Remote
PAY RANGE: $47.00 - $57.00/hr
DURATION: 6 months TOP 3 SKILLS:
- Proven experience in data engineering and data asset management.
- Proficiency in SQL, Python, and other relevant data processing languages and tools.
- Expertise in data modeling, ETL processes, and workflow orchestration (e.g., Airflow, Databricks).
COMPANY:
Our client a Fortune 500 Software Organization is seeking a Data Engineer 3 to bring onto the team.
Job Description:
Data Asset Inventory and Assessment
- Inventory of existing data assets; tables, dashboards, and pipelines
- Follow requirements to pull required data to measure the current state of these assets, set up usage metrics for internal and external stakeholders.
- To improve documentation coverage for tables, including table descriptions, column definitions, and data lineage.
- Implement a centralized metadata management system to maintain and access asset documentation.
- Ensure that all existing and new data assets are properly documented according to established standards.
- Consolidate and streamline pipelines by eliminating redundancies and unnecessary elements according to the set of provided rules.
- Clean up and restructure data tables, ensuring consistent naming conventions, data types, and schema definitions.
- Retire or archive obsolete dashboards and workflows.
- Implement monitoring and alerting mechanisms for critical workflows to ensure timely issue detection and resolution.
- Set up a foundation for scalable Data Model for the Stock Business - Implement and build performant data models to solve common analytics use-cases.
- Thoroughly document the work performed, including methodologies, decisions, and any scripts or tools developed.
- Provide comprehensive knowledge transfer to the data team, ensuring a smooth transition and the ability to maintain the optimized data environment.
- Proven experience in data engineering and data asset management.
- Proficiency in SQL, Python, and other relevant data processing languages and tools.
- Expertise in data modeling, ETL processes, and workflow orchestration (e.g., Airflow, Databricks).
- Strong analytical and problem-solving skills.
- Excellent communication and documentation abilities.
- Familiarity with cloud data platforms (e.g., Azure, AWS, GCP) is a plus.
IND123
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