Snowflake Data Engineer

Job highlights

• 2+ years experience with Snowflake, dbt, Apache Airflow, Python, SQL, AWS, and data warehousing
• Design and develop scalable ETL/ELT pipelines, build and maintain Snowflake data warehouses, manage Airflow DAGs, optimize queries, implement data security, lead and mentor engineers

We're Hiring: Lead Data Engineer

Location: Bhopal, Madhya Pradesh

Experience: 2+ Years

Work Mode: On-site

Employment Type: Full-time

About the Role

We are looking for an experienced Lead Data Engineer to design, build, and modernize enterprise-scale data platforms and lead the development of reliable, scalable, and secure data solutions.

The ideal candidate should have strong hands-on experience with Snowflake, dbt, Apache Airflow, Python, SQL, AWS/Azure, and modern data engineering practices. The role will also involve technical leadership, mentoring engineers, performance optimization, and driving data engineering best practices.

Key Responsibilities

Design and develop scalable ETL/ELT data pipelines for enterprise data platforms.

Build and maintain data warehouse solutions using Snowflake.

Develop modular and reusable transformation models using dbt Core/Cloud.

Design and manage Apache Airflow DAGs, scheduling, dependencies, retries, monitoring, and alerting.

Develop data processing and automation solutions using Python and advanced SQL.

Work with Fivetran and SnapLogic for multi-source data ingestion and integration.

Optimize Snowflake queries, warehouses, micro-partitioning, clustering, and overall cloud costs.

Implement data security using RBAC, IAM, KMS, Secrets Manager, data masking, and least-privilege access.

Develop automated data quality checks, reconciliation, schema validation, and monitoring frameworks.

Work with Databricks, PySpark, and Delta Lake for large-scale data processing.

Implement CI/CD and Infrastructure-as-Code practices using GitHub Actions and Terraform.

Conduct code reviews, establish coding standards, and mentor junior/mid-level data engineers.

Troubleshoot production pipeline failures and ensure data platform reliability.

Required Skills

Must Have:

2+ years of experience in Data Engineering

Strong hands-on experience with Snowflake

dbt Core/Cloud

Apache Airflow

Strong Python and Advanced SQL

Data warehousing and dimensional modeling

ETL/ELT pipeline development

AWS cloud services

Git and CI/CD

Good to Have:

Databricks / PySpark / Delta Lake

Fivetran / SnapLogic

Terraform

GitHub Actions

AWS IAM, KMS, S3, Lambda, CloudWatch

Data governance and security

Experience leading and mentoring data engineering teams

What We're Looking For

Strong ownership of production data platforms

Excellent problem-solving and troubleshooting skills

Ability to design scalable and maintainable data solutions

Strong understanding of data quality, security, and governance

Experience working in Agile/Scrum environments

Ability to mentor engineers and drive technical best practices

Why Join Us?

Work on modern cloud-based data engineering platforms

Opportunity to work with Snowflake, dbt, Airflow, Python, AWS, and Databricks

Lead enterprise-level data engineering initiatives

Collaborate with a growing engineering team

Opportunity to contribute to architecture, automation, and technical standards

Interested? Apply now or share your profile with us.

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