Sr. Data Engineers

iLink Digital•Bellevue, WA

2d•Remote

About The Position

Sr. Data Engineers establish and maintain centralized management of data across systems. They work with and review enterprise data, query and programming logic, troubleshoot issues, and provide remediation for short- and long-term solutions. They adopt consistent software-based data governance and data quality standards for existing and new data sources, and provide the business with insights that enable data-driven decision-making. The role standardizes data and metric definitions in alignment with business strategy and outcomes, and ensures the quality of data-related deliverables, including data onboarding, solutioning, reporting, and analytic readiness. Sr. Data Engineers work with business and analytic stakeholders to perform data and process gap analysis, drive data-processing automation supporting Analytics and Machine Learning Operations across internal data, and provide metadata, taxonomies, cross-references, and supplemental data needed to integrate other data sources. They use reports and data collection technology to investigate discrepancies and questionable data trends, oversee test data management, and develop test plans and automated test suites. The role is based at various and unanticipated worksites throughout the United States, with headquarters in Bellevue, Washington, and may be performed remotely. Salary is $135,000 per year, plus benefits.

Requirements

Bachelor's degree in Computer Science, Information Technology, or a related field.
At least 3 years of experience with data architecture, business intelligence (BI), or ETL.
At least 3 years of experience investigating data discrepancies, managing test data, developing test plans, writing SQL queries and stored procedures, and developing automated test suites.
Experience with Snowflake; AWS cloud services including S3, Glue, EMR, Lambda, Webhook, and Redshift; ETL tools Informatica and Talend; Teradata; Unix scripting; PySpark; and Jupyter Notebook data profiling.

Responsibilities

Establish and maintain centralized management of data across systems.
Review enterprise data, query and programming logic; troubleshoot issues and provide short- and long-term remediation solutions.
Adopt consistent software-based data governance and data quality standards for existing and new data sources.
Provide business insights to enable data-driven decision-making.
Standardize data and metric definitions in alignment with business strategy and outcomes.
Ensure the quality of data-related deliverables, including data onboarding, solutioning, reporting, and analytic readiness.
Work with business and analytic stakeholders to perform data and process gap analysis.
Drive data-processing automation supporting Analytics and Machine Learning Operations across internal data.
Provide metadata, taxonomies, cross-references, and supplemental data required to integrate other data sources.
Use reports and data collection technology to investigate data discrepancies and questionable data trends.
Oversee test data management and develop test plans and automated test suites.