Data Engineer I

POSITION OVERVIEW

The Data Engineer is responsible for designing and implementing the data and analysis infrastructure, as well as determining the appropriate data management systems for analysis. Data Engineer builds, maintains, and optimizes data pipelines, and moves these data pipelines effectively into production for key data consumers. Data Engineer also provides data expertise when building and testing stories, features, and components; and participates in the development and management of application programming interfaces (APIs) that access key data sources. The Data Engineer works to guarantee compliance with data governance and data security requirements while creating, improving, and operationalizing integrated and reusable data pipelines to enable faster data access, integrated data reuse, and improve time-to-solution for data initiatives.

The Data Engineer contributes to the development of the team backlog and architectural runway, management of work in process (WIP) levels, and support of engineering aspects of program and solution Kanban. Data Engineer may also participate in program increment planning, pre- and- post planning, system, and solution demos, and inspect and adapt events.

In addition to the Data Engineer's typical responsibilities, the Data Engineer could be expected to be part of the Agile Development Team.

ESSENTIAL JOB FUNCTIONS

• Assist in building and maintaining data pipelines and data management solutions using Snowflake, Coalesce, SQL, and Python.
• Assist in managing and monitoring data pipelines and workflows using Airflow and other orchestration technologies.
• Develop and support data transformation processes used to extract, transform, and load data between systems.
• Assist with data integrations, conversions, imports, and exports involving Workday and other internal and external systems.
• Assist in troubleshooting and resolving programming, pipeline, and production support issues while developing root-cause analysis skills.
• Learn and use modern data preparation, integration, automation, cloud, and AI-enabled tools and techniques.
• Assist in implementing processes that support data integrity, standardization, and quality.
• Contribute to data reliability, efficiency, quality, and automation improvements.
• Assist in maintaining data dictionaries, metadata, data mappings, technical specifications, test cases, and production support documentation.
• Work closely with product teams, engineers, analysts, and business partners to understand data requirements and contribute to the development of technical solutions.
• Participate in Agile Team activities and contribute to regularly producing product increments.
• Perform other duties as assigned.

EDUCATION & EXPERIENCE

Required

• Bachelor's degree in IT Engineering, Computer Science, Business Management, Mathematics, Information Technology, Computer Engineering, or Information Sciences preferred, or equivalent experience
• Typically requires 0-2 years of experience in the desired field or may have entry level technical or business work experience, including internships
• SQL experience.
• Python experience.
• Ability to troubleshoot programming and technical issues.
• Basic understanding of data engineering concepts.
• Basic understanding of data integration, data quality, and data transformation
• Problem-solving skills
• Ability to collaborate with business and IT stakeholders
• Ability and willingness to learn new technologies

Preferred or Specialized

• Experience in an agile environment strongly preferred
• Relevant certification is preferred

CERTIFICATIONS & LICENSES

• N/A

KNOWLEDGE, SKILLS & ABILITIES

Good to have requirements:

• Experience in an Agile environment.
• Experience or exposure to Snowflake, Coalesce, Workday, or Airflow.
• Relevant technical certification.
• ETL/ELT and data pipeline development
• REST APIs
• Agile methodologies
• DevOps concepts
• Data modeling
• Metadata management

Basic ability to:

• Learn and use advanced analytics tools for object-oriented/object function scripting
• Work across multiple deployment environments including cloud and on-premises, and multiple operating systems
• Work with popular data discovery, analytics, and business intelligence (BI) software tools for semantic-layer-based data discovery
• Collaborate with both business and IT stakeholders
• Use judgment to form conclusions that may challenge conventional wisdom
• Apply original thinking to produce new ideas and innovate

Basic knowledge of:

• Data management disciplines including data integration, modeling, optimization, and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks
• Popular database programming languages for relational and non-relational databases
• Representational state transfer (RESTful) API design
• Agile methodologies and capable of applying DevOps principles to data pipelines to improve the communication, integration, reuse, and automation of data flows

Applicants must be authorized to work in the U.S. without sponsorship now or in the future.

Pay Range:

• $73,000 - $98,000 per year
  
  • This range is based on the expected level of experience and skills for this position. Final compensation will depend on individual

Benefits:

• Health, Dental and Vision Insurance
• Generous 401(k) with company match
• Paid Time Off (PTO) with Paid Holidays
• Flexible/Hybrid Work Schedule
• Paid Volunteer Program

For more information about the benefits we offer, please visit our Careers Page.