Senior Database Engineer

YO It Consulting; Pune District; Hybrid; INR 1,500,000 - 2,000,000; Full time

Job summary

YO It Consulting is seeking a Senior Database Engineer in Pune, India, to optimize and automate cloud database solutions. The role demands 7-12 years of experience, expertise in Snowflake, PostgreSQL, AWS RDS, and proficiency in tools such as DBT and Terraform. You'll work with DevOps teams to develop scalable data architectures and ensure performance and reliability in data workflows. This hybrid position allows three days of work from the office, providing an engaging environment for skilled professionals.

Qualifications

• 7+ years of experience in data engineering or database engineering.
• Hands-on experience with Snowflake performance tuning and optimization.
• Expertise in PostgreSQL and AWS RDS in cloud-native architectures.
• Experience designing lakehouse or modern data warehouse architectures.

Responsibilities

• Architect and optimize scalable data platforms using Snowflake and PostgreSQL.
• Engineer reliable batch and near-real-time ELT pipelines using dbt.
• Manage infrastructure as code using Terraform with CI/CD-enabled deployments.

Skills

Cloud Database

AWS

Postgres

Snowflake

Oracle RDS

Medallion Architecture

DBT

AI/ML Solutions

Python

Database design

Tools

Terraform

SQL

Job description

Senior Database Engineer

Location: Pune
Experience: 7-12 years
Work Mode: Hybrid (3 Days WFO)

Must Haves

• Cloud Database
• AWS, Postgres, Snowflake, Oracle RDS
• Medallion Architecture
• DBT
• AI/ML Solutions
• Python
• Database design

Role Overview

Join our DevOps Engineering team as a Senior Database Engineer responsible for designing, optimizing, and automating cloud database solutions across AWS RDS, Postgres, and Snowflake. This role focuses on performance engineering, data integration, and automation - ensuring our data platforms are scalable, reliable, and efficient. You’ll work closely with DevOps and Product Engineering to build high-performing data infrastructure that supports critical applications and analytics.

Key Responsibilities

Modern Data Architecture & Platform Engineering

• Architect and optimize scalable data platforms using Snowflake, PostgreSQL, and Oracle RDS.
• Design cloud-native lakehouse architectures on AWS using Medallion (Bronze/Silver/Gold) patterns.
• Build hybrid systems spanning operational databases and analytical warehouses.
• Develop performant data models, ELT pipelines, semantic layers, and reusable metrics.
• Manage schema evolution, replication, partitioning, and lifecycle strategies for scalability and resilience.

Advanced Data Pipelines & Orchestration

• Engineer reliable batch and near-real-time ELT pipelines using dbt and cloud-native services.
• Implement data quality, schema validation, lineage, and observability.
• Optimize performance, scalability, and cost across data workflows.

AI-Enabled Data Engineering

• Apply AI/ML for anomaly detection, schema drift detection, and query optimization.
• Design AI-ready data foundations supporting feature stores and ML pipelines.
• Collaborate with Data Science teams to ensure reproducible, governed ML workflows.

Automation, DevOps & Governance

• Manage infrastructure as code using Terraform with CI/CD-enabled data deployments.
• Automate provisioning and monitoring using Python, SQL, and APIs.
• Implement enterprise-grade security, governance, RBAC, encryption, and compliance controls.

Required Skills & Experience

• 7+ years of experience in data engineering, database engineering, or data platform development in production environments.
• Strong hands-on experience with Snowflake, including performance tuning, security, and cost optimization.
• Deep expertise with PostgreSQL and AWS RDS in cloud-native architectures.
• Proven experience designing lakehouse or modern data warehouse architectures.
• Strong understanding of Medallion Architecture, semantic layers, and analytics engineering best practices.
• Experience building and operating advanced ELT pipelines using modern tooling (e.g., dbt, orchestration frameworks).
• Proficiency with SQL and Python for data transformation, automation, and tooling.
• Experience with Terraform and infrastructure-as-code for data platforms.
• Solid understanding of data governance, observability, and reliability engineering.