Job Description:
Job Description Details
Business Title
Data Engineer
Years of Experience
Min 3 and max upto 7.
Job Descreption
Looking for a hands‑on Senior Data Engineer – Azure & Databricks with up to 6 years of total experience to build, optimize, and maintain scalable cloud data platforms.
This is an individual contributor role, focused on developing reliable data pipelines and analytics‑ready datasets using Microsoft Azure and Databricks. The role requires strong hands‑on expertise in SQL and Python, along with experience building batch (and basic streaming) data pipelines in a cloud environment.
You will collaborate closely with architects, analytics teams, QA, DevOps, and business stakeholders in a global delivery model.
Must have skillsHands‑on experience delivering Azure‑based data engineering solutions
Cloud & Data Engineering (Azure)
Strong hands‑on experience with Azure data services, including:
Azure Data Lake Storage Gen2 (ADLS)
Azure Data Factory (ADF)
Azure Databricks
Azure Synapse Analytics
Experience designing cloud‑native data lakes and analytical data stores
Solid understanding of batch data pipelines and basic streaming concepts
SQL & Python (Mandatory)
Strong SQL skills (mandatory)
Writing complex queries, joins, aggregations, and transformations
Hands‑on experience working with large datasets in Synapse / Databricks
Strong Python skills (mandatory)
Python for ETL / ELT and data engineering use cases
Hands‑on experience with PySpark in Databricks
Strong understanding of data modeling, transformations, and query performance tuning
Data Processing & Engineering
Hands‑on experience with Spark / PySpark on Databricks
Experience handling structured and semi‑structured data
Understanding of partitioning, schema evolution, and data validation concepts
DevOps & Platform Basics
Working knowledge of Infrastructure as Code (ARM Templates and/or Terraform)
Basic experience with CI/CD pipelines (Azure DevOps or GitHub Actions)
Understanding of logging and monitoring using Azure Monitor / Log Analytics
Collaboration
Ability to work effectively with architects, QA, DevOps, and business stakeholders
Good communication skills for explaining technical concepts clearly
Good to have skillsExposure to streaming technologies such as Azure Event Hubs or Kafka
Familiarity with Lakehouse architecture and Delta Lake concepts
Experience integrating Azure data platforms with BI tools (Power BI preferred)
Basic knowledge of data governance and data quality frameworks
Awareness of Azure cost‑optimization best practices
Experience working in Agile delivery models, especially with global clients
Key responsibiltesData Engineering & Development
Build scalable ETL / ELT pipelines using Azure and Databricks
Develop SQL‑based transformations and Python / PySpark pipelines
Ingest and process data using ADF, Databricks, and ADLS
Build analytics‑ready data models optimized for performance and cost
Platform & Operations
Support deployment and execution of data pipelines across environments
Monitor data pipeline health, performance, and data quality
Troubleshoot pipeline failures and perform root‑cause analysis
Follow Azure security, reliability, and scalability best practices
Collaboration & Delivery
Work closely with architects and product teams to understand requirements
Translate business and analytics needs into working Azure data solutions
Contribute to documentation, code reviews, and engineering standards
Education Qulification
1. Bachelor’s or Master Degree or equivalent Degree
Certification If Any
1. Microsoft Certified: Fabric Data Engineer Associate
2.Microsoft Certified: Azure Solutions Architect Expert
3. Snowflake Core
Shift timing
12 PM to 9 PM and / or 2 PM to 11 PM - IST time zone
Location:
DGS India - Pune - Kharadi EON Free ZoneBrand:
MerkleTime Type:
Full timeContract Type:
PermanentSkills Required
- 3-7 years of relevant data engineering experience
- Strong SQL skills (complex queries, joins, aggregations, transformations)
- Strong Python skills for ETL/ELT and data engineering
- Hands-on experience with Spark / PySpark on Databricks
- Hands-on experience delivering Azure-based data engineering solutions
- Experience with Azure Data Lake Storage Gen2 (ADLS)
- Experience with Azure Data Factory (ADF)
- Experience with Azure Databricks
- Experience with Azure Synapse Analytics
- Understanding of batch data pipelines and basic streaming concepts
- Experience working with large datasets and performance tuning
- Working knowledge of Infrastructure as Code (ARM Templates and/or Terraform)
- Basic experience with CI/CD pipelines (Azure DevOps or GitHub Actions)
- Understanding of logging and monitoring using Azure Monitor / Log Analytics
- Bachelor's or Master's degree (or equivalent)
- Exposure to streaming technologies (Azure Event Hubs or Kafka)
- Familiarity with Lakehouse architecture and Delta Lake concepts
- Experience integrating Azure data platforms with BI tools (Power BI preferred)
- Basic knowledge of data governance and data quality frameworks
- Awareness of Azure cost-optimization best practices
- Experience working in Agile delivery models with global clients
- Microsoft certifications (Fabric Data Engineer Associate, Azure Solutions Architect, Snowflake Core)
dentsu Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about dentsu and has not been reviewed or approved by dentsu.
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Parental & Family Support — Paid parental leave at full pay and caregiver supports (including backup care) are emphasized as standout elements. Feedback suggests family-oriented benefits are a strong part of the package.
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Leave & Time Off Breadth — Flexible or unlimited PTO, extensive paid holidays, and a year-end office closure are established components. Feedback suggests time-off policies are generous and add meaningful flexibility.
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Retirement Support — A large, established 401(k) plan with employer matching is clearly documented. Feedback suggests retirement benefits feel competitive and straightforward.
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