Senior Data Engineer – Cloud‑Scale Data Lake Architecture, ETL Pipeline Development & Analytics Enablement (Remote, Customer Support Focus)

Remote, USA

Posted Jun 15, 2026

Full-time

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About arenaflex – Pioneering the Future of Cloud Data

arenaflex is a global technology leader that empowers millions of users every day with innovative cloud‑based solutions. From cutting‑edge data platforms to intelligent analytics services, arenaflex’s mission is to turn raw information into actionable insight, driving smarter decisions for businesses worldwide. Our culture blends relentless curiosity, collaborative spirit, and a commitment to continuous learning—making arenaflex the ideal place for engineers who want to shape the next generation of data infrastructure.

Role Overview

We are seeking a highly motivated Data Engineer to join our rapidly expanding Data Lake & Pipeline team. In this role you will partner with cross‑functional groups—including data scientists, product managers, and cloud architects—to design, build, and operate massive, petabyte‑scale data pipelines that power analytics, machine learning, and business intelligence across arenaflex’s cloud ecosystem. While the position is open to candidates with varying levels of experience, we value a strong foundation in data engineering best practices, a passion for building reliable systems, and an eagerness to grow within a supportive, fast‑moving environment.

Key Responsibilities

Collaborate with senior data engineers and product owners to translate business requirements into robust, scalable data pipelines.
Design, develop, and maintain ETL/ELT workflows using modern orchestration tools such as Airflow, Control‑M, or AWS Step Functions.
Implement data ingestion solutions that ingest structured and semi‑structured data from on‑premise sources, SaaS platforms, and multi‑cloud environments (AWS, GCP).
Build and optimize data models in relational databases (SQL) and NoSQL stores (e.g., DynamoDB, Cassandra, MongoDB) to support downstream analytics.
Ensure data quality, lineage, and governance by integrating validation frameworks, metadata tracking, and automated testing (unit, integration, end‑to‑end).
Develop containerized services using Docker and Kubernetes to enable portable, reproducible pipeline deployments.
Partner with data visualization teams to expose clean, reliable data through tools such as Tableau, QuickSight, Power BI, or Looker.
Monitor production pipelines, troubleshoot performance bottlenecks, and implement proactive alerting and incident response processes.
Document architecture decisions, data flow diagrams, and operational runbooks to foster knowledge sharing across the organization.
Participate in agile ceremonies, contribute to sprint planning, and provide estimates for new feature work.

Essential Qualifications

Education: Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related technical field. A master’s degree is a plus.
Experience: Minimum 2 years of hands‑on data engineering experience, including design and implementation of production‑grade ETL pipelines.
Programming Proficiency: Strong command of at least one high‑level language (Python, Java, or Scala) and solid SQL skills.
Data Modeling: Demonstrated ability to work with relational, columnar, and NoSQL data stores, understanding of schema design and indexing strategies.
Cloud Platforms: Practical experience with AWS or GCP services (S3, Redshift, BigQuery, Lambda, Dataflow, etc.) and familiarity with cloud‑native security and networking concepts.
Orchestration Tools: Experience using workflow orchestration tools such as Apache Airflow, Control‑M, or AWS Step Functions.
Containerization: Hands‑on exposure to Docker and Kubernetes for packaging and deploying data services.
Testing & CI/CD: Knowledge of software development lifecycle best practices, including unit testing, integration testing, and continuous integration pipelines.

Preferred Qualifications

Exposure to big‑data processing frameworks (Apache Spark, Flink, or Beam).
Experience with data cataloging and governance tools (AWS Glue Data Catalog, Apache Atlas).
Familiarity with data visualization platforms such as Tableau, Amazon QuickSight, QlikView, or IBM Cognos.
Understanding of data security and compliance standards (GDPR, HIPAA, SOC 2).
Previous work in a highly regulated industry or large‑scale e‑commerce environment.
Strong communication skills with a track record of translating technical concepts for non‑technical stakeholders.

Core Skills & Competencies

Analytical Mindset: Ability to dissect complex data problems, identify root causes, and propose elegant solutions.
Collaboration: Comfortable working in cross‑functional teams, building consensus, and sharing knowledge.
Adaptability: Thrive in a fast‑changing environment, quickly learning new tools and technologies.
Attention to Detail: Commitment to data accuracy, consistency, and reliability.
Customer‑Centric Focus: Understanding how data pipelines impact end‑user experiences and business outcomes.
Proactive Ownership: Taking initiative to identify improvement opportunities and driving them to completion.

Career Growth & Learning Opportunities

At arenaflex, your development is a priority. You will have access to:

Mentorship from senior data architects and industry experts.
Annual learning stipend for certifications, conferences, or online courses (e.g., AWS Certified Data Analytics, Google Cloud Professional Data Engineer).
Internal hackathons and innovation labs where you can prototype new data solutions.
Clear career pathways—from Data Engineer I to Lead Data Engineer, and eventually to Data Platform Architect.
Opportunities to work on high‑visibility projects that directly influence arenaflex’s product roadmap.

Work Environment & Culture at arenaflex

arenaflex fosters an inclusive, collaborative, and flexible work environment. Our teams are distributed globally, and we support remote work arrangements, flexible hours, and a results‑oriented culture. We celebrate diversity, encourage open dialogue, and provide resources for mental and physical well‑being. Whether you’re joining from a home office or a corporate hub, you’ll find a supportive community that values your ideas and respects your work‑life balance.

Compensation, Perks & Benefits

While exact compensation varies by location and experience, arenaflex offers a competitive salary package, performance‑based bonuses, and a comprehensive benefits suite that typically includes:

Medical, dental, and vision coverage for you and your dependents.
401(k) retirement plan with company match.
Employee Stock Purchase Plan (ESPP) allowing you to buy arenaflex shares at a discount.
Generous paid time off, sick leave, and parental leave policies.
Remote work stipend for home‑office equipment and internet costs.
Wellness programs, including mental‑health resources, fitness class reimbursements, and virtual wellness challenges.
Employee assistance program (EAP) for confidential counseling and support services.
Discounts on arenaflex products and services, as well as partner discounts on technology and travel.
On‑site amenities (where applicable) such as cafeterias, fitness centers, and collaborative lounges.

How to Apply

If you are excited about building data pipelines that power intelligent decision‑making at scale, we want to hear from you. Click the link below to submit your application, attach your resume, and share a brief cover letter outlining why you’re a great fit for arenaflex’s Data Engineering team.

Apply Now

Join arenaflex – Transform Data into Impact

At arenaflex, data is more than just numbers; it’s the foundation of every product, service, and strategic decision. By joining our Data Engineering team, you will help shape the future of data‑driven innovation, work alongside world‑class talent, and grow your career in a supportive, forward‑thinking environment. Take the next step in your professional journey—apply today and become part of a company that values curiosity, excellence, and impact.

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