Senior Data Engineer

Location

Experience

Team

Department

About Entri

Stability at Scale

Role Overview

Data Engineer

Product, Design, Finance, Legal, and Business

Key Responsibilities

• Build and Maintain Data Pipelines:

• Design, develop, and manage robust ETL/ELT pipelines using tools like

  Airbyte

  ,

  dbt

  , and

  Airflow

  to collect, clean, and transform data from multiple systems.

• Database Engineering:

• Work extensively with

  PostgreSQL

  , ensuring efficient schema design, performance tuning, and data modeling that support analytical workloads.

• Data Warehousing & Lakehouse:

• Design and manage scalable data models for

  Snowflake

  ,

  BigQuery

  , or other modern data warehousing solutions.

• Data Quality & Governance:

• Implement validation, testing, and monitoring systems to ensure data accuracy, lineage, and reliability across the platform.

• Cross-Functional Collaboration:

• Work closely with

  Product Managers

  ,

  Project Managers

  ,

  Designers

  ,

  Finance

  ,

  Legal

  , and

  Business teams

  to understand their data requirements and deliver solutions that support key decisions.

• Process Automation:

• Identify and automate manual data collection and reporting processes to improve operational efficiency.

• Modernization & Best Practices:

• Contribute to the modernization of Entri’s data platform by evaluating and integrating industry best practices, tools, and architectural improvements.

Required Skills & Qualifications

• Experience:

  3–5 years in Data Engineering or similar roles in fast-paced, data-intensive environments.

• Programming:

  Strong proficiency in

  Python

  and

  SQL

  .

• Databases:

  Experience with

  PostgreSQL

  (query optimization, schema design, and performance tuning).

• Data Stack:

  Hands-on experience with

  Airbyte

  ,

  dbt

  , and

  Airflow

  (or similar tools).

• Data Platforms:

  Exposure to

  Snowflake

  or

  BigQuery

  , with understanding of cloud-based data architectures.

• Data Modeling:

  Solid understanding of

  data warehousing

  ,

  data lakes

  , and

  data lakehouse

  concepts.

• Version Control & CI/CD:

  Familiarity with

  Git

  and modern DevOps practices for data workflows.

• Data Quality & Governance:

  Experience implementing or using frameworks for

  data validation

  and

  observability

  .

• Communication & Collaboration:

  Strong ability to translate technical concepts into business understanding and collaborate with non-engineering stakeholders.

Good to Have

• Experience with

  data observability tools

  like Great Expectations, Soda, or Monte Carlo.
• Exposure to

  real-time or streaming data

  (Kafka, Pub/Sub, etc.).
• Familiarity with

  data security, compliance, and governance

  principles.
• Interest in

  building foundations for future data science and analytics initiatives

  .

What We Offer

• A high-impact role shaping the data foundation for one of India’s fastest-growing EdTech companies.
• A collaborative environment with close partnerships across product, design, finance, and business functions.
• Opportunity to influence the modernization of Entri’s data stack and architecture.
• A culture that encourages experimentation, continuous learning, and professional growth.
• Competitive compensation, industry best work culture, and access to cutting-edge tools and technologies.