Data Engineer I

Pekin Insurance Careers•Pekin, IL

2d•Hybrid

About The Position

The Data Engineer designs and implements data and analysis infrastructure and determines appropriate data management systems for analysis. This role builds, maintains, and optimizes data pipelines and moves them into production for key data consumers. The Data Engineer provides data expertise for building and testing stories, features, and components, and participates in developing and managing APIs that access key data sources. The role helps ensure compliance with data governance and security requirements while developing and operationalizing integrated, reusable pipelines to enable faster data access and improve delivery of data initiatives. The Data Engineer contributes to team backlog development, architectural runway, work-in-process management, and engineering aspects of program and solution Kanban. The role may participate in program increment planning, planning events, demos, and inspect-and-adapt events, and may be part of an Agile Development Team. This position assists with data pipelines, transformations, integrations, quality, documentation, and production support, working with product teams, engineers, analysts, and business partners. It uses technologies including Snowflake, Coalesce, SQL, Python, and Airflow. The role is typically suited to someone with 0–2 years of experience or entry-level technical or business experience, including internships. A bachelor's degree in a relevant field or equivalent experience is preferred.

Requirements

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.
Typically 0–2 years of experience in the desired field, or entry-level technical or business work experience, including internships.
Applicants must be authorized to work in the U.S. without sponsorship now or in the future.

Nice To Haves

Bachelor's degree in IT Engineering, Computer Science, Business Management, Mathematics, Information Technology, Computer Engineering, or Information Sciences, or equivalent experience.
Experience in an Agile environment.
Experience or exposure to Snowflake, Coalesce, Workday, or Airflow.
Relevant technical certification.
Knowledge of ETL/ELT and data pipeline development, REST APIs, Agile methodologies, DevOps concepts, data modeling, and metadata management.
Ability to learn and use advanced analytics tools for object-oriented/object function scripting.
Ability to work across cloud and on-premises deployment environments and multiple operating systems.
Experience working with data discovery, analytics, and business intelligence software tools for semantic-layer-based data discovery.
Ability to use judgment to form conclusions that may challenge conventional wisdom and apply original thinking to innovate.
Knowledge of data management disciplines, relational and non-relational database programming languages, RESTful API design, Agile methodologies, and applying DevOps principles to data pipelines.

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 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 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.
Perform other duties as assigned.