Snowflake Data Engineer

Concord

Pune City

Hybrid

INR 1,200,000 - 1,800,000

Full time

14 days+

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Job summary

A leading company seeks a Senior Data Engineer to enhance their data infrastructure. This role involves designing scalable data pipelines, mentoring junior engineers, and implementing best practices in data modeling and governance. Ideal candidates will have extensive experience with Snowflake and dbt Cloud, along with strong SQL skills. Join a dynamic team in a hybrid work environment and make a significant impact on data-driven decision-making.

Qualifications

6+ years of hands-on experience in Data Engineering.
2+ years of experience using dbt Cloud.

Responsibilities

Lead the design and development of scalable data pipelines.
Optimize Snowflake performance and enforce data quality checks.

Skills

Data Engineering

SQL

Communication

Tools

Snowflake

dbt Cloud

Git

Airflow

Azure Data Factory

Job description

Direct message the job poster from Concord

Senior Executive @ SwiftWIN | Driving Talent Excellence | Data-Driven HR Leader | Award-Winning Professional

Location: Hybrid

Job Type: Full Time

Experience Level: Senior (6+ years)

About the Role:

We are looking for a Senior Data Engineer with deep expertise in Snowflake and dbt Cloud to design, build, and scale our data infrastructure. As a senior member of our data team, you will play a critical role in transforming raw data into usable insights by creating optimized pipelines, modular data models, and high-performance transformations. You will also mentor junior engineers and help define best practices across the data platform.

Key Responsibilities:

Lead the design and development of scalable data pipelines and ETL/ELT processes in Snowflake using dbt Cloud.
Architect and maintain modular, version-controlled, and testable dbt models aligned with business goals.
Optimize Snowflake performance by applying warehouse tuning, partitioning, clustering, and query optimization techniques.
Build and enforce data quality checks, data documentation, and testing strategies in dbt.
Collaborate with data analysts, scientists, and business teams to understand needs and deliver clean, accurate, and timely data.
Define and implement best practices for data modeling, data governance, security (RBAC), and cost optimization in Snowflake.
Lead and mentor junior engineers on coding standards, dbt conventions, and Snowflake best practices.
Drive integration of dbt with orchestration platforms (e.g., Airflow, Azure Data Factory) and CI/CD pipelines.

Required Qualifications:

6+ years of hands-on experience in Data Engineering, with at least 3+ years working with Snowflake.
2+ years of experience using dbt Cloud (dbt Core also acceptable if well-versed with dbt best practices).
Advanced SQL expertise for data modeling, transformation, and performance tuning.
Strong understanding of dimensional modeling, data warehouse design, and ETL/ELT processes.
Proficiency with Git, CI/CD, and automated testing frameworks in a dbt environment.
Experience working in a cloud ecosystem (AWS, Azure, or GCP) with data ingestion and orchestration tools.
Knowledge of Snowflake Streams, Tasks, Snowpipe, and other advanced Snowflake features.
Excellent communication and stakeholder management skills.

Preferred Qualifications:

Snowflake and/or dbt certification.
Experience with data observability tools like Monte Carlo, Datafold, or Great Expectations.
Familiarity with Fivetran, Airbyte, or Kafka for data ingestion.
Exposure to BI tools such as Power BI, Looker, or Tableau.
Knowledge of data privacy and compliance (GDPR, HIPAA, etc.).

Seniority level