Data Engineer I

Pekin Insurance•Pekin, IL

2d•$73,000 - $98,000•Hybrid

About The Position

The Data Engineer designs and implements data and analysis infrastructure and helps determine suitable data management systems for analysis. The role builds, maintains, and optimizes data pipelines and moves them into production for key data consumers. It provides data expertise for building and testing stories, features, and components and participates in developing and managing APIs that access key data sources. The Data Engineer supports compliance with data governance and security requirements and creates, improves, and operationalizes integrated, reusable pipelines to accelerate data access and reuse and improve time-to-solution for data initiatives. The role contributes to the team backlog and architectural runway, manages work in process levels, and supports engineering aspects of program and solution Kanban. It may also participate in program increment planning, planning events, system and solution demos, and inspect-and-adapt events. The Data Engineer may be part of an Agile Development Team. In this entry-level role, the employee assists with data pipelines and management solutions using Snowflake, Coalesce, SQL, and Python; workflow orchestration using Airflow and related technologies; data transformation and integrations; troubleshooting and production support; and improvements to data integrity, quality, reliability, efficiency, and automation. The role also maintains data documentation and collaborates with product teams, engineers, analysts, and business partners to understand requirements and contribute to technical solutions.

Requirements

Bachelor’s degree in IT Engineering, Computer Science, Business Management, Mathematics, Information Technology, Computer Engineering, or Information Sciences preferred, or equivalent experience.
Typically 0–2 years of experience in the desired field, or 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.
Applicants must be authorized to work in the U.S. without sponsorship now or in the future.

Nice To Haves

Experience in an Agile environment is strongly preferred.
Relevant certification is preferred.
Experience or exposure to Snowflake, Coalesce, Workday, or Airflow.
ETL/ELT and data pipeline development.
REST APIs and RESTful API design.
Agile methodologies and DevOps concepts.
Data modeling and metadata management.
Ability to learn and use advanced analytics tools for object-oriented or object-function scripting.
Ability to work across cloud and on-premises deployment environments and multiple operating systems.
Familiarity with data discovery, analytics, and business intelligence software for semantic-layer-based data discovery.
Knowledge of data management disciplines, including data integration, modeling, optimization, and data quality.
Knowledge of popular database programming languages for relational and non-relational databases.
Ability to apply DevOps principles to data pipelines to improve communication, integration, reuse, and automation of data flows.
Ability to use judgment to form conclusions that may challenge conventional wisdom and apply original thinking to produce new ideas and innovate.

Responsibilities

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 that 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 improvements in data reliability, efficiency, quality, and automation.
Assist in maintaining data dictionaries, metadata, data mappings, technical specifications, test cases, and production support documentation.
Work with product teams, engineers, analysts, and business partners to understand data requirements and contribute to technical solutions.
Participate in Agile Team activities and contribute to regularly producing product increments.
Contribute to the team backlog and architectural runway, manage work in process levels, and support engineering aspects of program and solution Kanban.
Perform other duties as assigned.