Senior Data Engineer – Retail Data Platforms & Analytics (Remote – California) – arenaflex
About arenaflex
arenaflex is a global leader in retail technology, delivering innovative data‑driven solutions that empower millions of shoppers and merchants every day. With a heritage of transforming the retail experience through cutting‑edge analytics, cloud‑native architectures, and a relentless focus on customer value, arenaflex is shaping the future of commerce. Our mission is to turn massive volumes of retail data into actionable insights that drive smarter decisions, improve operational efficiency, and create delightful experiences for both shoppers and partners.
Why This Role Matters
As a Data Engineer on the Data Ventures team, you will be at the heart of arenaflex’s data ecosystem. You’ll design, build, and maintain robust data pipelines that feed critical analytics and machine‑learning models used across the organization. Your work will directly influence how arenaflex anticipates market trends, optimizes inventory, personalizes offers, and ultimately delivers a seamless shopping experience for billions of customers worldwide.
Key Responsibilities
- Data Ingestion & Transformation: Consolidate disparate data sources, design scalable ETL/ELT pipelines, and ensure data is transformed into clean, reliable, and business‑ready formats.
- Data Modeling & Architecture: Create logical and physical data models, develop data warehouse schemas, and maintain data lake structures that support both batch and real‑time analytics.
- Pipeline Orchestration: Leverage tools such as Airflow, Prefect, or Cloud Composer to schedule, monitor, and troubleshoot complex data workflows.
- Performance Optimization: Tune queries, optimize storage formats (Parquet, ORC), and implement partitioning and indexing strategies to achieve sub‑second latency for high‑frequency reporting.
- Collaboration & Stakeholder Management: Partner with data scientists, business analysts, product owners, and engineering teams to translate business requirements into technical solutions.
- Quality Assurance & Testing: Develop automated unit, integration, and regression tests for data pipelines; enforce data quality rules and implement monitoring dashboards.
- Documentation & Knowledge Sharing: Maintain comprehensive documentation, contribute to internal wikis, and mentor junior engineers on best practices.
- Innovation & Continuous Improvement: Stay abreast of emerging technologies (e.g., Delta Lake, Dataflow, Snowflake) and propose enhancements that increase scalability, reliability, and cost efficiency.
Essential Qualifications
- Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent practical experience).
- 3+ years of professional experience building data pipelines in a cloud environment (GCP, AWS, or Azure).
- Proficiency in at least one programming language such as Python, Scala, or Java, with a strong emphasis on PySpark or Spark‑SQL.
- Hands‑on experience with distributed processing frameworks (Hadoop, Spark) and streaming platforms (Kafka, Pub/Sub).
- Solid understanding of relational databases (PostgreSQL, MySQL) and NoSQL technologies (Bigtable, MongoDB, Cassandra).
- Familiarity with data warehousing concepts, dimensional modeling, and BI tools (Looker, Tableau, Power BI).
- Demonstrated ability to design and implement end‑to‑end data solutions that meet performance, security, and compliance requirements.
Preferred Qualifications
- Experience with GCP services such as BigQuery, Dataflow, Dataproc, and Cloud Storage.
- Exposure to modern data orchestration tools like Apache Airflow, Dagster, or Prefect.
- Knowledge of containerization (Docker) and orchestration (Kubernetes) for data workloads.
- Familiarity with CI/CD pipelines for data engineering (GitLab CI, Jenkins, Cloud Build).
- Hands‑on experience with Databricks, Delta Lake, or similar lakehouse architectures.
- Strong analytical mindset with the ability to translate complex business problems into scalable data solutions.
- Excellent communication skills and a collaborative, mentorship‑oriented attitude.
Core Skills & Competencies
- Technical Acumen: Mastery of SQL, data modeling, and cloud‑native data services.
- Problem‑Solving: Ability to diagnose pipeline failures, root‑cause data quality issues, and propose robust fixes.
- Teamwork: Proven track record of working in cross‑functional, agile teams and influencing stakeholders without direct authority.
- Adaptability: Comfortable navigating a fast‑paced environment where priorities shift based on business needs.
- Continuous Learning: Commitment to staying current with industry trends, open‑source projects, and best practices.
Career Growth & Learning Opportunities
arenaflex invests heavily in employee development. As a Data Engineer, you will have access to:
- Mentorship programs with senior architects and data scientists.
- Sponsored certifications (e.g., Google Cloud Professional Data Engineer, AWS Certified Big Data).
- Internal hackathons and innovation labs where you can prototype new data products.
- Rotational assignments across different business units (e‑commerce, supply chain, finance) to broaden your domain expertise.
- Leadership pathways that can lead to Senior Engineer, Data Platform Lead, or Architecture roles.
Work Environment & Culture
arenaflex embraces a hybrid work model that blends remote flexibility with collaborative in‑office days. Our culture is built on:
- Inclusivity: A diverse workforce where every voice is heard and valued.
- Innovation First: We encourage experimentation, rapid prototyping, and learning from failure.
- Customer‑Centricity: All technical decisions are evaluated against the impact they have on our shoppers and merchants.
- Transparency: Open communication channels with leadership, regular town‑halls, and clear career roadmaps.
- Well‑Being: Flexible hours, mental‑health resources, and a supportive community that promotes work‑life harmony.
Compensation, Perks & Benefits
arenaflex offers a competitive total rewards package that includes:
- Base salary in the range of $70,000 – $80,000 USD per year, commensurate with experience.
- Annual performance bonuses tied to individual and company outcomes.
- Equity participation through stock purchase plans.
- Comprehensive health, dental, and vision coverage.
- 401(k) retirement plan with company match.
- Generous paid time off, parental leave, and flexible holidays.
- Professional development stipend for conferences, courses, and certifications.
- Remote‑work allowance for home office setup and internet expenses.
How to Apply
If you are passionate about turning massive retail data into strategic advantage and thrive in a collaborative, fast‑moving environment, we want to hear from you. Follow these steps to submit your application:
- Prepare an up‑to‑date resume highlighting relevant data engineering experience.
- Attach a copy of your degree certificate and any professional certifications.
- Include a brief cover letter explaining why arenaflex’s mission resonates with you and how your skill set aligns with the role.
- Submit your application through the official arenaflex careers portal (link provided below).
Join arenaflex and Shape the Future of Retail
At arenaflex, your code will power the decisions that affect millions of lives every day. You’ll work alongside some of the brightest minds in data, AI, and retail, all while enjoying the flexibility of remote work and the support of a company that values growth, diversity, and impact. Ready to make a difference? Apply now and become a catalyst for change in the world’s largest retail ecosystem.
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