Enterprise Data- Data Engineer I

GBU Life; Pittsburgh (Allegheny County); On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

Medical, Dental, Vision

Company paid HRA

401(k) + match

Pension Plan

Disability Insurance

Life Insurance

PTO & VTO (Volunteer Time Off)

Job summary

GBU Life is seeking a Data Engineer in Pittsburgh to design and maintain scalable data pipelines and infrastructure that enable BI, analytics, reporting, and data-driven decision making across the organization.

You will collaborate with data architects, analysts, scientists, and business stakeholders to deliver accurate, accessible, and trusted enterprise data, leveraging Snowflake and cloud technologies.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, Data Science, or a related field.
• 0 to 2 years of experience in data engineering, software development, or related field.
• Internship or academic projects may be considered in lieu of professional experience.
• Foundational understanding of relational databases, data structures, data integration, and data warehousing concepts.
• Demonstrated ability to learn new technologies, tools, and concepts.

Responsibilities

• Design, develop, test, deploy, and maintain scalable ETL/ELT pipelines.
• Develop and maintain data integration solutions for enterprise reporting and analytics.
• Contribute to scalable data models, databases, data warehouses, and data platforms.
• Support Snowflake data platform including data integration, structures, and architecture.
• Ensure data accuracy, security, and governance in line with standards.
• Develop automated testing and validation to prevent data quality issues.
• Monitor, troubleshoot, and optimize data pipelines for high availability and performance.
• Collaborate with architects and engineers to implement enterprise data architecture.
• Translate business requirements into technical data solutions.
• Integrate data from databases, apps, APIs, and external sources.

Skills

SQL proficiency

Python/Java/Scala basics

Analytical thinking

Problem solving

Team collaboration

Education

Bachelor's degree in Computer Science or related field

Tools

Snowflake

AWS/Azure/GCP basics

Git

Airflow

Job description

Job Summary

The Data Engineer is responsible for designing, developing, implementing, and maintaining scalable and reliable data pipelines and infrastructure that support GBU Life’s enterprise data initiatives. This position plays an important role in enabling business intelligence, analytics, reporting, and data driven decision making across the organization.

The Data Engineer works collaboratively with data architects, data analysts, data scientists, software engineers, and business stakeholders to understand data requirements and develop solutions that provide accurate, accessible, secure, and trusted enterprise data.

This position supports the ongoing development of GBU Life’s data architecture and enterprise data environment, including the Snowflake data platform. The Data Engineer applies data engineering principles, cloud technologies, automation, and best practices to improve the availability, quality, performance, and usability of organizational data.

DUTIES AND RESPONSIBILITIES

• Design, develop, test, deploy, and maintain scalable ETL/ELT pipelines to ingest, transform, and load data from multiple internal and external sources.
• Develop and maintain data integration solutions that support enterprise reporting, business intelligence, analytics, and operational needs.
• Contribute to the design and development of scalable data models, databases, data warehouses, and data platforms.
• Support the Snowflake data platform, including data integration, data structures, performance, and data architecture.
• Ensure data is accurate, reliable, secure, and accessible in accordance with established data quality, security, governance, and compliance standards.
• Develop automated testing and validation processes to identify and prevent data quality issues.
• Implement monitoring and alerting processes for data pipelines and proactively identify and resolve failures or performance issues.
• Monitor, troubleshoot, and optimize data pipelines to maintain high availability, reliability, and performance.
• Collaborate with data architects and other technology professionals to implement enterprise data architecture and standards.
• Partner with data analysts, data scientists, software engineers, and business stakeholders to understand data requirements and translate business needs into technical data solutions.
• Integrate data from databases, applications, APIs, and other enterprise and external sources.
• Work with structured and semi structured data, including JSON and XML formats.
• Develop and maintain technical documentation related to data architecture, data pipelines, data models, workflows, and processes.
• Utilize version control and software development best practices to manage data engineering code and solutions.
• Participate in the evaluation, implementation, and adoption of emerging data engineering and cloud technologies.
• Identify opportunities to improve data processes through automation, standardization, and optimization.
• Support data governance and enterprise data management initiatives.
• Maintain knowledge of current data engineering technologies, methodologies, and industry best practices.
• Properly adheres to company risk management principles: o Adhering to and supporting GBU’s Enterprise Risk Management Framework.
• Understanding and complying with applicable laws, regulations, policies and procedures; completing all required training; executing and monitoring controls effectively (as applicable); appropriately identifying, assessing, escalating and remediating risks, potential issues and control failures (as applicable); and reporting compliance or regulatory concerns to management. oUnderstanding and conducting oneself in accordance with the Employee Handbook and preserving GBU’s brand and reputation.
• Perform other duties as assigned.

QUALIFICATIONS

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, Data Science, or a related field; equivalent education, training, or experience may be considered.
• 0 to 2 years of experience in data engineering, software development, database development, analytics, or a related technical field.
• Internship, academic, co op, project, or hands on experience involving data, programming, databases, or technology may be considered in lieu of professional experience.
• Foundational understanding of relational databases, data structures, data integration, and data warehousing concepts.
• Demonstrated ability to learn new technologies, tools, and technical concepts.

PREFERRED QUALIFACTIONS

• Working knowledge of SQL and relational database concepts.
• Basic programming experience with Python, Java, or Scala.
• Foundational understanding of ETL/ELT processes and data integration concepts.
• Basic understanding of data modeling, data warehousing, and dimensional modeling.
• Exposure to or familiarity with Snowflake or other cloud based data platforms is a plus.
• Exposure to cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP) is a plus.
• Familiarity with data orchestration or workflow tools such as Apache Airflow or similar technologies is a plus.
• Basic knowledge of Git or other version control systems.
• Familiarity with Linux/Unix environments is a plus.
• Basic understanding of REST APIs and structured or semi structured data formats, including JSON and XML.
• Understanding of basic data quality, data integrity, data security, and data governance principles.
• Familiarity with software development practices such as testing, debugging, documentation, and version control.
• Ability to troubleshoot technical issues and investigate data discrepancies.
• Strong analytical and problem solving skills.
• Strong attention to detail and commitment to data accuracy.
• Effective written and verbal communication skills.
• Ability to collaborate with technical and business team members.
• Ability to organize work, manage priorities, and meet established deadlines.
• Demonstrated curiosity and interest in developing a career in data engineering and enterprise technology.
• Exposure to Snowflake, cloud data platforms, or modern data engineering technologies.
• Experience completing a data related academic or personal project using SQL, Python, or another programming language.
• Relevant entry level certifications or coursework in AWS, Azure, GCP, Snowflake, data engineering, databases, or related technologies.
• Exposure to the insurance, financial services, or other regulated industries.

OUR BENEFITS

• Medical, Dental Vision
• Company paid HRA
• 401(k) + match
• Pension Plan
• Long Term and Short Term Disability
• Life Insurance and ADD
• PTO and VTO (Volunteer Time Off)