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Senior Data Engineer | Snowflake | Azure | Python | Remote

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Remote

Senior Data Engineer | Snowflake | Azure | Python | Remote

Cogenthub

Senior Data Engineer | Snowflake | Azure | Python | Remote

Skills

SQL QueriesData EngineeringPythonC#.NETSnowflakeDatabricksData AnalysisAzure

1 month ago

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Important information


Contract type:

Permanent

Salary:

₹2,000,000 – ₹2,500,000 / year

Location:

Hyderabad, Telangana, India

Work mode:

Remote

Published on:

15 September 2026

What they need


SENIOR DATA ENGINEER SNOWFLAKE | AZURE | PYTHON

Job Details

Job Title: Senior Data Engineer
Work Mode: Remote / Work From Home
Experience: 6+ Years
CTC: 23-25 LPA
Shift: US Night Shift

Job Summary

We are seeking a highly hands-on Senior Data Engineer to join the data engineering team and take ownership of designing, architecting, building, and optimizing complex Snowflake-based data platforms and pipelines.

This is a high-ownership Individual Contributor position. The engineer will be expected to independently design end-to-end data systems, evaluate architectural tradeoffs, establish technical standards, and build scalable solutions across the Snowflake + Azure + Python ecosystem.

The ideal candidate should be capable of contributing immediately without requiring significant ramp-up on Snowflake.

Key Responsibilities

  • Architect, design, and build complex raw-file ingestion pipelines into Snowflake.
    • Build end-to-end data pipelines from ingestion through transformation and downstream processing.
    • Use Azure Data Factory (ADF) for orchestration and Python as a primary development language.
    • Write, optimize, and maintain complex Snowflake SQL queries, warehouses, and data models.
    • Build transformations primarily using dbt.
    • Perform Snowflake administration, including user/role management, access controls, warehouse sizing, resource monitors, and usage/performance monitoring.
    • Design, build, and support Azure Functions for event-driven and scheduled data processing.
    • Architect solutions using Azure Event Hubs for streaming and event ingestion.
    • Design and maintain Git-based CI/CD pipelines for data engineering code and deployments.
    • Evaluate competing technical and architectural approaches and make sound design decisions independently.
    • Translate ambiguous business requirements into scalable technical architectures and implementation plans.
    • Document system architecture, data flows, technical decisions, and engineering standards.
    • Partner with engineering, analytics, and business stakeholders to deliver reliable enterprise data solutions.
    • Take end-to-end ownership of complex data systems including development, optimization, troubleshooting, and production support.

Mandatory Skills

Candidates must have demonstrable hands-on professional/project experience with:

  • Snowflake querying, data modeling, performance tuning
    • Strong SQL / Snowflake SQL
    • Python data pipelines and automation
    • Microsoft Azure
    • Azure Data Factory (ADF)
    • Azure Functions
    • ETL / ELT pipeline development
    • Data Warehousing / Data Modeling
    • Git / CI/CD
    • End-to-end data engineering architecture and development
    • Strong Individual Contributor / ownership mindset

Preferred Skills

  • Snowflake Administration
    • dbt
    • Azure Event Hubs
    • Azure DevOps / ADO
    • Data platform architecture at scale
    • Performance and cost optimization
    • .NET / C#
    • SOLID principles and software architecture
    • Streaming / event-driven architecture

Critical Screening Requirement

Please read before applying:

This is a Snowflake-focused Senior Data Engineer position.

Candidates must have hands-on Snowflake experience demonstrated in their actual professional/project experience.

Databricks experience alone will NOT be considered equivalent to Snowflake experience.

Candidates should also have strong Python experience and practical Azure experience, with Azure Functions and Azure Data Factory being particularly important.

We are looking for engineers who can independently architect, design, build, administer, and support complex data systems rather than candidates whose experience is primarily in reporting, analytics, DevOps, or Databricks-only data engineering.

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