Data Engineer

A-dec Inc.•Newberg, OR

18d

About The Position

The position is responsible for expanding and optimizing the data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The Data Engineer(s) will support our software developers, data architect, and data analysts on data initiatives. You must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing the company's data warehouse to support the next generation of products and data initiatives.

Requirements

Bachelor's degree in Computer Science or related technical field or equivalent practical experience.
2+ years of experience in Information Technology with a focus on Business Applications, Data Engineering, Data Architecture, Data Analytics and Science.
Good understanding of data warehousing and Business Intelligence environments.
Excellent problem solving, critical thinking, and communication skills.
Experience with distributed source code version control system (e.g. git).
Experience with ticketing system (ServiceNow; JIRA etc.).
Expertise with Python, databases, and SQL expertise.
Strong analytic skills related to working with unstructured datasets.
Experience with data pipeline and workflow management tools

Nice To Haves

Experience with Azure environment such as Synapse, Azure SQL DB, Azure ML Pipeline, Azure Data Factory.
Knowledge of machine learning and data science processes.
Experience building reports and dashboards using BI tools.
Basic knowledge of statistics.
Stellar communications skills for requirements gathering

Responsibilities

Build both real-time and batch data integrations from disparate source systems into the EDW.
Work with data and analytics experts to strive for superior functionality in our data systems.
Write complex queries for reporting and the application consumption.
Assemble large, complex data sets that meet functional and non-functional business requirements.
Design and implement real-time ETL and batch processing of information to support modeling and reporting needs.
Provide production support for data integration and transformation pipelines.
Scale and tune data pipelines, databases, and SQL queries.
Build and maintain data reconciliation processes.
Responsible for finding trends in data sets and developing algorithms to help make raw data more useful to the enterprise.
Connect data to users in mixed cloud and on-prem environments.
Identify ways to improve data reliability, efficiency, and quality.
Partner with data architect & analysts to support modeling and reporting needs and to build and maintain internal data processing and visualization.
Translate requests into replicable analytic reports using varying applications.
Create tools to serve data such as APIs and packages, as needed.
Troubleshoot and provide root cause analysis for database software and data integrity issues