Data Engineer - (Snowflake + Azure)

Dentsu Global Services; Bengaluru; On-site; INR 3,000,000 - 5,400,000; Full time

Job summary

Dentsu Global Services in Bengaluru seeks a Technical Lead with deep hands‑on experience in cloud data platforms to design, develop, and optimize scalable data solutions. You will build robust pipelines, implement modern data platforms, and contribute to solution designs while supporting pre‑sales and client discussions.

The ideal candidate is a seasoned developer who can work independently on complex data engineering problems and collaborate with architects, stakeholders, and junior engineers.

Qualifications

• 7–10 years of hands-on data engineering experience.
• Hands-on with AWS and/or Azure and/or GCP data services; any 2 cloud platforms required.
• Expertise in ETL/ELT, data warehousing, and lakehouse architectures.
• Strong Python development for data engineering and automation.
• Experience with SaaS-based data platforms (Databricks, Snowflake).
• Experience implementing MDM solutions (Informatica, Reltio, Profisee).
• Knowledge of data governance, security and compliance in cloud.
• Exposure to AI concepts in data automation and orchestration.
• Ability to design and optimize scalable data pipelines and performance.
• Experience with query optimization and cloud cost control.
• Experience supporting analytics, BI, and downstream consumption.
• Strong communication to collaborate with architects, QA, DevOps, and stakeholders.

Responsibilities

• Design, develop, and maintain robust, scalable data pipelines across AWS, Azure, and GCP.
• Write high‑quality Python and SQL; implement ETL/ELT processes and data transformations.
• Collaborate with solution architects to implement data architectures and provide design inputs.
• Support pre‑sales with technical inputs, PoCs, demos, and prototype solutions.
• Implement data quality, governance, security controls, and compliance in solutions.
• Work with cross‑functional teams to translate requirements into technical implementations.
• Guide and mentor junior developers, conduct code reviews, promote best practices.
• Stay current with cloud, data engineering, and AI technologies and suggest improvements.

Skills

Python development

Data modeling

ETL/ELT pipeline development

Data warehousing

Cloud data platforms

SQL

Data governance

Communication

Automation

Scalable data pipelines

BI/Data analytics support

Tools

AWS

Azure

GCP

BigQuery

Synapse

Redshift

Databricks

Snowflake

Informatica

Reltio

Profisee

Job description

Job Description

Technical Lead with strong hands‑on experience in cloud-based data platforms (AWS, Azure, GCP) to design, develop, and optimize scalable data solutions.

This role focuses on building robust data pipelines, implementing modern data platforms, contributing to solution designs, and supporting pre‑sales and client discussions. The ideal candidate is a seasoned developer who can work independently on complex data engineering problems while collaborating closely with architects, stakeholders, and junior engineers.

Must have skills

7–10 years of hands‑on experience in data engineering and development roles.

Strong hands‑on experience with AWS and/or Azure and/or GCP data services such as BigQuery, Synapse, Redshift, Databricks, etc. Any 2 cloud experience is mandatory.

Solid expertise in data modeling, ETL/ELT pipeline development, data warehousing, and lakehouse architectures.

Strong Python development skills for data engineering, automation, orchestration, and solution prototyping.

Extensive experience working with SaaS‑based data platforms (e.g., Databricks, Snowflake, managed analytics services).

Experience implementing and integrating Master Data Management (MDM) solutions such as Informatica, Reltio, Profisee, or equivalent tools.

Practical knowledge of data governance, security, access control, and compliance requirements in cloud environments.

Basic exposure to Agentic AI concepts, such as AI‑driven automation, data orchestration, or intelligent workflow augmentation.

Ability to design, build, and optimize scalable and high-performance data pipelines.

Experience in query optimization, performance tuning, and cost optimization across cloud data platforms.

Hands‑on experience supporting analytics, BI, and downstream consumption layers.

Strong verbal and written communication skills to effectively collaborate with architects, QA, DevOps, and business stakeholders.

Ability to explain complex technical concepts clearly to non‑technical audiences.

Good to have skills

Familiarity with AI/ML integration into data platforms and analytics workflows.

Prior experience working in a consulting or professional services environment.

Key responsibilities

Design, develop, and maintain robust, scalable, and secure data pipelines and platforms across AWS, Azure, and GCP.

Write high-quality, maintainable code in Python and SQL; implement ETL/ELT processes and data transformations.

Collaborate with solution architects to implement approved data architectures and provide development‑level design inputs.

Support pre‑sales efforts by contributing to technical inputs, building PoCs, demos, and solution prototypes when required.

Implement data quality checks, governance standards, security controls, and compliance requirements in developed solutions.

Work closely with cross‑functional teams to understand requirements and translate them into effective technical implementations.

Guide and mentor junior developers, conduct code reviews, and promote best practices within the team.

Stay current with emerging cloud, data engineering, and AI technologies and recommend improvements to existing platforms.