Job Profile: Senior Data Analyst
Location: Gurgaon
Experience: 2-5 years
About: Fairdeal.Market
Fairdeal.Market is a rapidly growing B2B quick commerce company offering a wide range of products with delivery times as short as 60 minutes. Our mission is to ensure that every shopping bag worldwide can be filled efficiently and sustainably.
About The Role
We are looking for a Senior Data Analyst who thrives at the intersection of data engineering, analytics, and data science. You will be a foundational member of our data team, responsible for building a robust Data Warehouse, defining the single source of truth for key business metrics, and laying the groundwork for intelligent, self-serve analytics across the organisation.
If you have worked in a fast-paced startup environment and love owning end-to-end data problems from pipeline design to business insights this role is for you.
Key Data Problems We Are Solving
- Building a single source of truth for all key metrics in our organization.
- Building a robust Data Warehouse for a seamless data pipeline
- Demand Planning at SKU level
- Fill Rate Modelling at the supply level
What You Will Do
Data Engineering
- Design and implement scalable data pipelines that ingest, transform, and load data into the Data warehouse (Snowflake)
- Set up proactive alerts to detect bugs, anomalies, and data drift in pipelines before they affect downstream consumers
- Define data granularity and accuracy requirements in collaboration with engineering and product teams
Analytics & Data Warehousing
- Establish a Single Source of Truth for all key business metrics standardizing definitions, logic, and computation across teams
- Design Fact Tables and Dimension Tables to support efficient reporting and self-serve analytics
- Build and maintain dbt models for clean, version-controlled, and well-documented data transformations
- Partner with stakeholders to translate business questions into analytical frameworks and dashboards
Data Science
- Apply foundational data science techniques to support demand planning including trend analysis, seasonality decomposition, and simple forecasting models
- Define and document target variables, accuracy metrics, and model evaluation criteria
- Monitor model performance in production and flag degradation proactively
What We Are Looking For
Experience
- 25 years of overall experience in Analytics, Data Engineering, Business Intelligence, or a related field
- Prior experience as an analyst at a startup is strongly preferred we value ownership, scrappiness, and bias for action
Technical Skills
- SQL advanced querying, query optimization, and schema design (Mandatory)
- Python for data transformation, automation, and light modelling (Mandatory)
- Data Warehousing strong grasp of dimensional modelling, Fact and Dimension tables, slowly changing dimensions
- Data Pipelines hands-on experience building or maintaining ETL/ELT workflows
- dbt experience writing, testing, and documenting dbt models
- Alerting & Monitoring experience setting up data quality checks and pipeline alerts
- Basic Data Science familiarity with regression, time-series, or forecasting techniques for demand planning
Mindset & Approach
- Strong ownership mentality you see a problem through from discovery to production
- Comfort with ambiguity and rapidly changing requirements
- Ability to communicate complex data concepts clearly to non-technical stakeholders
- Passion for building things that last clean, documented, and scalable
Skills Snapshot
SQL (Advanced)Pythondbt
Data WarehousingFact Table DesignETL / ELT Pipelines
Pipeline AutomationAlerting & MonitoringSingle Source of Truth
Demand Planning BasicsData ModellingStartup Experience
Good to Have
- Experience with cloud data warehouses such as BigQuery, Snowflake, or Redshift
- Familiarity with orchestration tools like Airflow or Prefect
- Exposure to BI tools such as Metabase, Looker, or Superset
- Background in marketplace, logistics, or on-demand service businesses
What You Can Expect
- High ownership from day one you will shape how data works at this company
- Direct impact on product and business decisions through data
- A fast-moving environment with short feedback loops and room to experiment
- Mentorship and collaboration with experienced data and product leaders
- Opportunity to build the data function from the ground up
