Job Description:
Job Description
Details
Business Title
Lead Developer/Engineer
Years of Experience
Min 6 and max upto 10.
Job Descreption
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
Core Technical 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 responsibiltes
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.
Education Qulification
1. Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
Certification If Any
AWS Data Analytics / Solutions Architect
Azure Data Engineer Associate
GCP Professional Data Engineer
SnowPro Core Certification
Any two of the above
Databricks, Snowflake, or other cloud data platform certifications are a plus.
Shift timing
12 PM to 9 PM and / or 2 PM to 11 PM - IST time zone
Location:
DGS India - Pune - Indiqube OrchidBrand:
MerkleTime Type:
Full timeContract Type:
PermanentSkills Required
- 7-10 years of hands-on experience in data engineering and development roles
- Hands-on experience with at least two of AWS, Azure, and GCP
- Experience with cloud data services such as BigQuery, Synapse, Redshift, or Databricks
- Expertise in data modeling, ETL/ELT pipeline development, data warehousing, and lakehouse architectures
- Strong Python development skills for data engineering, automation, orchestration, or prototyping
- Extensive experience with SaaS-based data platforms such as Databricks or Snowflake
- Experience implementing or integrating Master Data Management solutions such as Informatica, Reltio, or Profisee
- Knowledge of data governance, security, access control, and cloud compliance requirements
- Basic exposure to Agentic AI concepts
- Experience designing, building, and optimizing scalable, high-performance data pipelines
- Experience with query optimization, performance tuning, and cloud cost optimization
- Experience supporting analytics, BI, and downstream consumption layers
- Strong verbal and written communication skills
- Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related field
- Any two relevant certifications, including AWS Data Analytics or Solutions Architect, Azure Data Engineer Associate, GCP Professional Data Engineer, or SnowPro Core
- Familiarity with AI/ML integration into data platforms and analytics workflows
- Experience in consulting or professional services
- Databricks, Snowflake, or other cloud data platform certifications
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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