Senior Data Analyst

About the job

Es Magico builds AI agents that actually work in production. We're a Mumbai and Bengaluru-based team creating custom AI workflows for enterprises in finance, healthcare, entertainment, and education. Think intelligent automation that handles real business tasks—from customer support to hiring to learning and development to calls to document processing to complex decision-making. We also partner with early-stage startups as a venture builder, helping them ship AI-native products from 0 to 1. We are seeking a full-time Senior Data Analyst to be the founding member of our data team. Till today our AI engineering team has been duelling as a data analyst as well. We are now at a stage where we need a trained expert to guide us and take our AI solutions to the next level. As our first data hire, you'll clean up the foundations for how we collect, clean, curate, and prepare data to finetune our models and SLMs. This role is focused on creating high-quality training datasets, building annotation workflows, evaluating model outputs, and ensuring data quality across our AI systems. You'll work closely with leadership, AI engineering, product, and business teams to understand requirements and translate them into structured datasets. 3+ years in data analysis, data engineering, or related roles with strong focus on data quality and ML applications • Expert-level proficiency in Python and data manipulation libraries (Pandas, NumPy, Polars) • Strong SQL skills and experience working with both structured and unstructured data • Hands-on experience creating training datasets for ML/LLM finetuning including data cleaning, labeling, and validation • Understanding of what makes quality training data: diversity, balance, edge cases, and domain coverage • Experience designing and managing data annotation processes, working with annotation tools and labeling workflows • Familiarity with data versioning, dataset management, and maintaining data lineage • Strong analytical and problem-solving skills with attention to detail and data integrity • Ability to communicate insights and collaborate across technical and non-technical teams • Experience with LLM evaluation frameworks and creating eval datasets • Familiarity with prompt engineering and understanding how data quality impacts model performance • Knowledge of domain-specific data requirements in BFSI, healthcare, or enterprise contexts • Understanding of synthetic data generation and data augmentation techniques • Familiarity with observability and monitoring tools (Langfuse, DataDog, etc.) • Background in building ETL/ELT pipelines and data workflows • Experience with unstructured data: documents, transcripts, images, audio

Requirements

• Python
• SQL
• Data Quality

Preferred Technologies

• Python
• SQL
• Data Quality