Senior Data Analyst

About SkyCell: SkyCell is an award-winning, purpose-driven pharmaceutical logistics scale-up engineering next-generation smart container systems and digital platforms to protect global healthcare supply chains. Backed by a Platinum EcoVadis rating highlighting our dedication to structural sustainability, we utilize cutting-edge IoT sensor arrays and data-driven infrastructure to ensure life-saving medicines are distributed efficiently, safely, and with zero carbon waste across more than 40 countries.

Position Overview

We are seeking a curious, hands-on Senior Data Analyst to join our Data Platforms & Analytics team. In this specialized systems infrastructure track, you will be responsible for transforming complex, large-scale time-series, hardware sensor, and event-driven operational datasets into high-signal actionable insights. Leveraging Python and PySpark libraries within Databricks systems, you will build scalable analytics pipelines, quantify measurement correction metrics, isolate telemetry anomalies, and curate production-ready datasets to fuel our upstream Artificial Intelligence (AI) and Retrieval-Augmented Generation (RAG) platform layers.

Key Responsibilities

• Time-Series Sensor Analytics: Ingest, optimize, and analyze high-volume streaming sensor data and operational log frames using advanced Python and PySpark workflows.
• Anomaly & Trend Isolation: Construct automated statistical logic to detect hardware measurement drifts, performance deviations, and anomalies across distributed tracking points.
• SQL Query Performance Tuning: Write and refactor high-performance complex SQL and SparkSQL scripts leveraging comprehensive analytical window functions and window partition trees.
• AI & RAG Ingestion Preparation: Format, cleanse, and structure messy operational data arrays into curated, high-value asset registries tailored for machine learning model training.
• BI Dashboard Engineering: Architect reusable data visualization assets and self-service reporting portals within enterprise business intelligence platforms.
• Incident Root-Cause Investigation: Act as a premier technical advisory resource during live operational incidents, executing rapid data analysis to isolate infrastructural failure modes.

Required Skills & Qualifications

• Bachelor’s degree in Data Science, Computer Science, Statistics, or a closely related quantitative engineering discipline; a Master’s degree is considered a profound technical advantage.
• Advanced, authority-grade SQL script architecture skills, showcasing a deep tracking background writing complex analytical joins and sub-queries.
• Strong programming expertise leveraging Python and PySpark to manage large-scale data manipulation workflows.
• Demonstrated history parsing complex streaming datasets, including IoT telemetry, time-series intervals, or event-driven logs.
• Familiarity navigating modern distributed computing clusters and BI ecosystems, specifically Databricks, Spark, and Power BI.
• Outstanding stakeholder communication mechanics, with an innate capability to translate dense algorithmic trends into clear corporate growth guidelines.
• Location Context: Remote-friendly framework open specifically to qualified technical analysts permanently residing within India, with regional office infrastructure hubs available in Hyderabad.
• Work Authorization: Valid local work authorization is mandatory; this role is completely ineligible for immigration visa sponsorship.

What We Offer

• The exceptional professional canvas to deploy big-data analytics and shape sustainable logistics solutions for the global healthcare ecosystem.
• Highly competitive compensation package calibrated accurately against your PySpark engineering depth and data analysis portfolio.
• Flexible working hours built entirely around work-life balance, asynchronous execution trust, and remote-friendly collaboration parameters.
• Immersive onboarding support via SkyWeek, our dedicated cross-functional corporate culture alignment matrix.
• Generous maternity and paternity leave structures coupled with a comprehensive annual leave allocation index.