Senior Scale Operations & Data Analyst – Data Engineering, Analytics, and Data Entry Specialist

html About arenaflex arenaflex is a forward‑thinking technology partner that empowers businesses to transform data into decisive action. With a portfolio that spans dynamic e‑commerce platforms, cutting‑edge reputed company, and next‑generation analytics services, arenaflex is at the forefront of the data revolution. Our mission is simple: turn raw information into strategic advantage. We do this by building robust data pipelines, delivering actionable insights, and fostering a culture of curiosity and continuous improvement. Role Overview As a Senior Scale Operations & Data Analyst, you will be the linchpin that connects data science, engineering, and business strategy. You will own the end‑to‑end data lifecycle—from ingestion and cleansing to modeling and storytelling—while also ensuring that our scale operations run with precision and efficiency. This is a full‑time, hybrid role that blends analytical rigor with hands‑on operational excellence. Why arenaflex? • Work with a high‑impact team that shapes product strategy and drives revenue growth. • Access to state‑of‑the‑art tools (SQL, Python, R, Tableau, Power BI, reputed company, dbt). • Opportunities for continuous learning—internal bootcamps, conference sponsorships, and mentorship. • A culture that celebrates innovation, collaboration, and transparency. • Competitive salary, equity, and comprehensive benefits package. Key Responsibilities • Data Engineering & Operations – Design, implement, and maintain scalable data pipelines that ingest, transform, and store data from multiple sources. • Advanced Analytics – Apply statistical techniques, machine learning models, and hypothesis testing to uncover trends, forecast demand, and recommend optimizations. • Performance Metrics & Dashboards – Build and maintain real‑time dashboards that track key performance indicators (KPIs) for product, marketing, and finance teams. • A/B Testing & Experimentation – Design, run, and analyze experiments to validate product changes and marketing initiatives. • Data Quality & Governance – Identify data integrity issues, develop remediation plans, and enforce data governance policies. • Stakeholder Collaboration – Translate business questions into data requirements, present findings, and influence decision‑making across the organization. • Documentation & Knowledge Sharing – Create clear documentation for data pipelines, models, and dashboards; conduct training sessions for non‑technical teams. Essential Qualifications • Minimum 1 year of professional experience in data analysis, preferably within the digital media, e‑commerce, or technology sector. • Proficiency in SQL for data extraction and manipulation. • Hands‑on experience with Python or R for data wrangling, statistical analysis, and model development. • Strong foundation in statistical modeling, hypothesis testing, and experimental design. • Experience with data visualization tools such as Tableau, Power BI, or Looker. • Excellent communication skills—capable of translating complex data insights into actionable business recommendations. • Team player with a reputed company, solution‑oriented mindset. Preferred Qualifications • Experience with ETL/ELT frameworks (e.g., dbt, Airflow, reputed company). • Knowledge of cloud data platforms (reputed company, BigQuery, Redshift). • Familiarity with machine learning libraries (scikit‑learn, TensorFlow, PyTorch). • Background in product analytics or growth hacking. • Prior exposure to scalable web infrastructure (Kubernetes, Docker). • Experience in a fast‑paced startup environment with cross‑functional teams. Skills & Competencies • Analytical Thinking – Ability to dissect complex problems and derive data‑driven solutions. • Technical Proficiency – Comfortable writing clean, maintainable code and SQL queries. • Business Acumen – Understand how data insights translate into revenue, cost savings, or customer experience improvements. • Project Management – Prioritize tasks, manage timelines, and deliver high‑quality outputs under tight deadlines. • Collaboration & Influ