**Job Title:** Senior Data Engineer – Logistics Business Intelligence & Cloud Data Pipeline Development

• *Job Description:**

Join arenaflex: Where Innovation Meets Impact

Are you ready to be part of one of the world's most respected retail organizations? Welcome to arenaflex — a global leader in wholesale retail operations spanning fourteen countries, serving millions of members and continuing to grow at an unprecedented pace. Despite our scale and remarkable international expansion, arenaflex remains committed to a family-oriented, employee-driven culture where individuals thrive and build meaningful careers. In fact, arenaflex has been recognized as one of the top employers globally, ranking seventh in Forbes' "World's Best Employers" list — a testament to our unwavering dedication to our workforce.

Now, we are looking for a talented and passionate Data Engineer – Logistics Business Intelligence to join our dynamic Technology team. This is a unique opportunity to work at the intersection of data engineering, cloud technology, and retail innovation. You will be responsible for building and operationalizing end-to-end data pipelines that power arenaflex's Logistics reporting capabilities, serving as the backbone for critical business decisions that impact operations across the globe.

Why arenaflex?

At arenaflex, we believe that our people are our greatest asset. We foster an environment where creativity, collaboration, and continuous learning are celebrated. When you join arenaflex, you become part of a community that values integrity, customer service, and operational excellence. We offer competitive compensation, comprehensive benefits, and ample opportunities for professional growth and advancement. Whether you are just starting your career or looking to take the next big step, arenaflex provides the platform and support you need to succeed.

Position Overview

The Data Engineer – Logistics Business Intelligence will be responsible for designing, building, and maintaining automated data pipelines that transform raw data from multiple internal and external sources into actionable insights. This role is central to our data engineering efforts, focusing on creating robust, scalable, and high-quality data solutions that support strategic decision-making across the organization. You will collaborate closely with product owners, engineering teams, and data platform specialists to ensure the reliability and efficiency of our data infrastructure.

Key Responsibilities

• Pipeline Development & Operations: Create and operationalize data pipelines to make data readily available for consumption by the Logistics Business Intelligence team. Design, build, test, and automate pipelines that serve as the single source of truth across the organization.


• Collaboration & Architecture: Work alongside data architects and BI engineers to design efficient data pipelines, providing recommendations for ongoing optimization of data storage, ingestion, quality, and integration.


• ETL/ELT Implementation: Plan, develop, and implement ETL/ELT processes using IICS (Informatica Cloud) and other modern data integration tools to ensure seamless data flow between systems.


• Cloud Technology Utilization: Leverage Microsoft Azure services including Azure SQL Data Warehouse (Synapse), Azure Data Lake Storage (ADLS), Azure Event Hub, and Azure Data Factory to enhance and accelerate the delivery of data products and services.


• Big Data & NoSQL Solutions: Implement big data and NoSQL solutions by developing scalable data processing platforms that drive high-value insights for the organization.


• Process Improvement: Identify, plan, and execute internal process improvements, including automating manual processes and streamlining data delivery workflows to increase operational efficiency.


• Data Quality & Reliability: Continuously identify ways to improve data reliability, efficiency, and overall quality of data management practices.


• Technical Communication: Convey complex technical concepts to non-technical audiences effectively, both in written documentation and verbal presentations.


• Peer Review & Mentorship: Perform peer reviews for other data engineers' work, providing constructive feedback and fostering a culture of excellence and knowledge sharing.

Essential Qualifications

• Experience: Minimum 2+ years of experience designing and operationalizing data pipelines with large and complex datasets.


• Tools Expertise: 2+ years of experience with Informatica PowerCenter and Informatica IICS (Intelligent Cloud Services).


• Cloud Experience: 2+ years of experience working with cloud technologies, including ADLS, Azure Databricks, Spark, Azure Synapse, Cosmos DB, and other big data technologies.


• Data Engineering Skills: 2+ years of experience in Data Modeling, ETL, and Data Warehousing concepts and implementation.


• Integration Techniques: 2+ years of experience implementing data integration techniques such as event/message-based integration (Kafka, Azure Event Hub).


• DevOps Practices: 2+ years of experience with Git and Azure DevOps for version control and CI/CD pipelines.


• Data Sources: Extensive experience working with diverse data sources including SQL, SQL Server databases, flat files (CSV, delimited formats), Web APIs, and XML.


• Advanced SQL: Strong SQL skills with a deep understanding of relational databases, business data, and the ability to write complex SQL queries across multiple data sources.


• Database Concepts: Solid understanding of database storage concepts including Data Lake, Relational Databases, NoSQL, Graph databases, and Data Warehousing.


• Agile Environment: Ability to thrive in a fast-paced agile development environment, managing multiple priorities and delivering results under tight deadlines.

Preferred Qualifications

• Microsoft Azure certifications or similar cloud platform credentials.


• Experience delivering data solutions through agile software development methodologies.


• Proficiency in scripting languages such as PowerShell or Python for automation and data processing.


• Experience with UC4 Job Scheduler or similar workflow automation tools.


• Familiarity with the retail industry and its unique data challenges and opportunities.


• Excellent verbal and written communication skills, with the ability to translate technical concepts for diverse audiences.


• Bachelor's degree in Computer Science, Engineering, or equivalent software/services experience.

Skills & Competencies Required for Success

• Technical Proficiency: Deep expertise in data engineering tools, cloud platforms, and programming languages commonly used in modern data architectures.


• Problem-Solving: Strong analytical abilities to identify data challenges and develop innovative, effective solutions.


• Collaboration: Excellent teamwork skills with the ability to work effectively across functional teams and communicate with stakeholders at all levels.


• Attention to Detail: Meticulous approach to data quality, testing, and documentation to ensure accuracy and reliability.


• Adaptability: Willingness to learn new technologies and adapt to evolving business requirements in a dynamic industry.


• Leadership Potential: Ability to mentor junior team members and contribute to best practices within the data engineering community.

Career Growth & Learning Opportunities

At arenaflex, we invest heavily in the professional development of our employees. As a Data Engineer joining our team, you will have access to:

• Comprehensive training programs and certifications in cutting-edge cloud technologies.


• Mentorship from senior engineers and industry experts.


• Exposure to enterprise-scale data architectures and cross-functional projects.


• Clear career progression pathways toward senior technical roles, team leadership, or specialized data architecture positions.


• Internal mobility opportunities across different business units and geographies.


• Continuous learning through workshops, conferences, and knowledge-sharing sessions.

Work Environment & Culture

arenaflex offers a collaborative, inclusive work environment where diversity is celebrated and innovation is encouraged. Our team members enjoy:

• Flexible work arrangements and modern office amenities.


• A supportive culture that promotes work-life balance.


• Team-building activities and employee recognition programs.


• Access to employee wellness programs and resources.


• The chance to make a tangible impact on a globally recognized brand.

Compensation & Benefits

We recognize that our employees deserve competitive compensation and comprehensive benefits. The Data Engineer position offers:

• Hourly Rate: $26.00 per hour (commensurate with experience and qualifications).


• Full-Time Employment: 8-hour workdays in a permanent, full-time capacity.


• Health & Wellness: Comprehensive health, dental, and vision insurance options.


• Retirement Plans: 401(k) retirement savings plan with company matching.


• Paid Time Off: Generous paid vacation, sick leave, and holiday entitlements.


• Employee Discounts: Exclusive discounts on arenaflex products and services.


• Career Development: Tuition reimbursement and professional development opportunities.

Location

This position is based in Chicago, USA, with potential for hybrid or remote work arrangements based on business needs and team preferences.

Join Us

If you are passionate about data engineering, thrive in collaborative environments, and want to contribute to one of the world's most admired companies, we want to hear from you! At arenaflex, your skills and dedication will be rewarded with a fulfilling career, outstanding benefits, and the chance to shape the future of retail technology.

Simply apply online today and take the first step toward reimagining your career. Join arenaflex — where innovation meets impact, and your journey truly begins.

arenaflex is an equal opportunity employer and values diversity in the workplace. We do not discriminate based on race, color, religion, national origin, sex, age, disability, genetic information, or any other protected characteristic. All employment decisions are based on qualifications, merit, and business needs.