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Data Engineer

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Onsite

Data Engineer

Pepagora

Data Engineer

Skills

SQL QueriesData EngineeringPythonKafkaData AnalysisAIAWSdbtApache Airflow

1 month ago

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Important information


Contract type:

Permanent

Salary:

₹1,000,000 – ₹1,400,000 / year

Location:

Coimbatore, Tamil Nadu, India

Work mode:

Onsite

Published on:

15 September 2026

What they need


Pepagora India Pvt Ltd
Data Engineer - Job Description
BUILD INTELLIGENCE

Location: Coimbatore | Work Mode: Full-time, In-Office

Millions of businesses and products are only useful when the data can be trusted.

About Pepagora

Pepagora is trust infrastructure for global B2B growth. We operate a verification-first ecosystem that reduces trust friction, improves deal velocity, and enables SMEs to expand across borders with confidence. Our core product system - TruBadge, ESR Score, Janu AI, and OneInbox - powers signal-driven decision-making for businesses worldwide. Incorporated in Singapore, Pepagora is at a Pre-Series A stage and scaling rapidly across international markets.

About the Role

Build the data foundation behind ingestion, enrichment, entity resolution, analytics, search and AI. Make data observable, governed and usable by product systems - not trapped in one-off scripts.

What You'll Be Doing

  • Design ingestion and transformation pipelines
  • Build reliable canonical datasets and data-quality checks
  • Support entity resolution, enrichment and feature generation
  • Create datasets/interfaces for search, analytics and AI
  • Implement lineage, monitoring, backfills and failure recovery
  • Partner with backend and AI engineers on data contracts

Who We're Looking For:

  • Typically 4 - 7 years in data engineering or data-platform roles
  • Strong SQL and Python
  • Experience building production ETL/ELT pipelines
  • Solid data modelling and data-quality fundamentals
  • Cloud data/storage experience and operational ownership

Good to Have:

  • Airflow/Dagster/dbt or similar
  • Spark/large-scale processing
  • Kafka/event streaming
  • Data lake/warehouse architectures
  • Search/vector data pipelines

Technology Environment

Python • SQL • ETL/ELT • AWS • orchestration • data quality • observability

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