Lead Data Engineer (AWS) | Mumbai | Immediate Joiners Preferred

JD for Lead Data Engineer (AWS) for Mumbai - local candidates preferred

Is this you?

This is for you if:

• You have 6+ years of genuine, hands-on Data Engineering experience built specifically on AWS (Glue, Lambda, EMR, Redshift, S3),

• You're comfortable being the first technical hire on a new client engagement

• You've led or mentored engineers even without a formal "Lead" title,

• You're either based in Mumbai or ready to relocate immediately for a full-time, work-from-office role.

This is NOT for you if:

-Your core background is DevOps/SRE, BI/Reporting, or Business Analysis with AWS only listed as a skill rather than shown in your actual project work

-Your hands-on cloud experience is primarily Azure or GCP; you need more than 30 days' notice

-You're not seriously open to relocating to Mumbai.

Please don't apply in above cases, it saves everyone's time on both sides.

Positions Open: 6

Employment Type: Full-time, Permanent on clients payroll

Locations: Mumbai (Lower Parel or Airoli) candidates can be considered for either

Work Mode: Hybrid, 3 days a week WFO

Notice Period: Immediate joiners strongly preferred; maximum 1 month notice accepted ( non-negotiable)

Hiring Timeline: Fast-track closure please apply only if you can commit to a quick interview process

There may be minimum 3 virtual/ in-person rounds post successful initial online tech assessment CBT test.

This opportunity is being hired for one of NurimTechs strategic partners, engaged through our talent partnership channel.

About the Role

We are seeking a highly skilled, delivery-focused Lead Data Engineer to design and build enterprise-grade data platforms and applications on new implementation engagements. This is a hands-on leadership role, responsible for leading end-to-end build and development initiatives, architecting scalable data pipelines, and delivering cloud-native solutions on AWS. You will act as a key technical leader on new client engagements often the first person onboarded to a new team working closely with client stakeholders to translate business requirements into robust data engineering solutions.

Key Responsibilities

Solution Design & Implementation

• Lead end-to-end design and development of scalable, high-performance data engineering solutions.
• Architect and implement new data pipelines, data models, and cloud-native data platforms.
• Design modular, reusable, future-ready data frameworks for enterprise use cases.
• Translate client requirements into technical designs in direct collaboration with stakeholders.

Technical Leadership

• Provide architectural direction for new data platform development and modernization initiatives.
• Define best practices for ETL/ELT design, data modeling, and cloud-native data processing.
• Build and optimize data pipelines using AWS services (Glue, Lambda, Redshift, S3, EMR, Athena, etc.).
• Leverage PySpark, SQL, Python, and distributed processing frameworks for large-scale data processing.
• Drive engineering excellence through code quality, performance tuning, and scalable design patterns.

Agile Delivery & Execution

• Lead sprint planning, estimation, and delivery of development milestones in Agile environments.
• Ensure timely delivery of high-quality data engineering components.
• Collaborate with cross-functional product, analytics, and infrastructure teams.

Client Engagement & Solutioning

• Act as technical advisor for clients during solution design and implementation.
• Present architecture approaches, design decisions, and trade-offs to stakeholders.
• Proactively recommend solutions to improve scalability, performance, and business value.

Team Leadership & Mentoring

• Lead and mentor a team of data engineers; often the first hire on a new engagement, responsible for helping build out the team.
• Drive task allocation, design reviews, and technical guidance.
• Build an engineering culture focused on ownership and continuous improvement.

Process, Quality & Governance

• Establish CI/CD pipelines, version control practices, and automated testing frameworks.
• Ensure adherence to coding standards, documentation, and design governance.
• Identify risks and dependencies early; implement mitigation strategies.

Required Skills & Qualifications

• 6+ years of hands-on, core Data Engineering experience on AWS this must be genuine, hands-on pipeline/platform work, not adjacent roles.
• Strong hands-on expertise in AWS cloud services: Glue, Lambda, Redshift, S3, Athena, EMR, CloudWatch.
• Strong proficiency in PySpark, SQL, and Python for large-scale data processing.
• Proven experience designing and building end-to-end data pipelines and data platforms.
• Deep understanding of distributed data processing and performance optimization.
• Proven experience leading engineering teams (3+ years), ideally on development/implementation projects.
• Strong client-facing and communication skills.
• Experience with Agile delivery methodologies.
• Familiarity with JIRA, Confluence, Git, Jenkins, or equivalent CI/CD tooling.

Good to Have

• Experience in greenfield data platform development or AWS migration projects.
• Exposure to legacy-to-cloud transformation programs.
• Strong understanding of data modeling concepts and Hive/partitioning strategies.
• Experience building real-time or near-real-time data pipelines.

Eligibility Note

Candidates who dont currently hold a Lead title but have 6+ years of core Data Engineering experience, and have mentored/managed junior engineers or are currently performing equivalent responsibilities, are welcome to apply.

Please review this JD carefully before applying - only apply if your experience genuinely aligns with the core requirements above, so we can move quickly to interviews.