Senior Data Engineer

BookMyMentor; Gurgaon; On-site; INR 1,200,000 - 2,000,000; Full time

Job summary

BookMyMentor is hiring for a Data Engineer to design, build, and maintain scalable data pipelines for Fairdeal.Market, a growing B2B quick commerce company. The role requires strong proficiency in Apache Kafka, Flink, and Spark Streaming, along with SQL and Python skills.

The ideal candidate will have 5–9 years of experience in high-velocity environments and will be responsible for ensuring data quality and driving improvements across key metrics.

Qualifications

• 5–9 years of experience building production-grade data pipelines.
• Strong understanding of distributed systems principles.
• Experience with data orchestration tools such as Airflow or Prefect.

Responsibilities

• Design and maintain scalable data pipelines.
• Architect and evolve the data lakehouse.
• Ensure data quality and SLA monitoring end-to-end.

Skills

Data pipeline development

Apache Kafka

Apache Flink

Spark Streaming

SQL proficiency

Python proficiency

Data modeling

Education

Bachelor's degree in Computer Science or related field

Tools

BigQuery

Redshift

Snowflake

Job description

Fairdeal.Market is a rapidly growing B2B quick commerce company offering a wide range of products with delivery times as fast as 60 minutes. Our mission is to ensure that every shopping bag worldwide can be filled efficiently and sustainably. As we continue to scale, we are building a strong data backbone to power speed, accuracy, and intelligence across operations – from warehouse to last mile.

Responsibilities

1. Design, build, and maintain scalable, fault‑tolerant data pipelines handling high‑velocity event streams across the Fairdeal.Market ecosystem; own the full data lifecycle from ingestion to serving with a focus on reliability, low latency, and cost efficiency.
2. Architect and evolve our data lakehouse – including ingestion, storage, transformation, and serving layers; drive standardization of data models across OLAP and OLTP systems; maintain clean, well‑documented schemas and enforce data contracts.
3. Build and manage real‑time data streams using Kafka, Flink, or Spark Streaming to power operational dashboards, ML feature pipelines, and alerting systems; ensure exactly‑once semantics and resilient recovery at scale.
4. Own data quality, SLA monitoring, and pipeline observability end‑to‑end; implement data validation frameworks, anomaly detection, and alerting; establish a culture of data reliability across the team.
5. Partner closely with product, ML, data science, and business intelligence teams to surface the right data at the right latency; translate complex operational and product requirements into efficient, scalable data solutions.
6. Continuously evaluate data tooling across the stack – from orchestration and transformation to storage and serving; make structured build‑vs‑buy recommendations with a focus on developer productivity and long‑term scalability.
7. Mentor junior data engineers, conduct design reviews, and raise the bar for engineering practices on the team; contribute to a culture of documentation, code quality, and knowledge sharing.

KPI Ownership: Own and drive improvements across key data platform metrics, including pipeline uptime and SLA adherence, data freshness and latency, data quality and accuracy scores, infrastructure cost per event processed, mean time to detect and resolve data incidents, and query performance across analytical workloads.

Requirements

• Bachelor's degree in Computer Science, Engineering, or a related field; an advanced degree is a plus.
• 5–9 years of experience building production‑grade data pipelines, with at least 3 years at significant scale (tens of millions of events per day).
• Prior experience in e‑commerce, quick commerce, fintech, or other high‑velocity consumer tech environments strongly preferred.
• Proven track record of architecting and scaling distributed data systems end‑to‑end – from design to production.
• Deep expertise in at least one streaming framework: Apache Kafka, Apache Flink, or Spark Streaming.
• Strong SQL and Python proficiency; comfort with a JVM language (Scala or Java) is a bonus.
• Hands‑on experience with cloud data warehouses: BigQuery, Redshift, Snowflake, or ClickHouse.
• Solid understanding of distributed systems principles – partitioning, replication, consistency, and exactly‑once semantics.
• Experience with data orchestration tools such as Airflow, Prefect, or Dagster.
• Familiarity with data transformation frameworks (dbt) and open table formats (Delta Lake, Apache Iceberg).
• Strong understanding of data modeling for both analytical (star/snowflake schema) and operational workloads.
• Systems thinker who can connect warehouse operations, product event data, and downstream ML pipelines into a coherent architecture.
• Comfortable working both hands‑on in the codebase and in strategic infrastructure discussions with engineering leadership.
• Highly ownership‑driven with the ability to manage ambiguity and drive execution in a fast‑paced environment.
• Sensitivity to Real India constraints – low‑bandwidth environments, device diversity, and cost efficiency for emerging market scale.

About the Company

FairDeal.Market transforms how India's Kirana stores shop by empowering local retailers with better prices, faster deliveries, and full transparency. Using smart technology, efficient logistics, and deep local insight, we ensure stores can order seamlessly and stay stocked every day, allowing them to thrive with the speed and scale of modern commerce.