Technical Lead /Data Analytics & Cloud

Nxtwave Disruptive Technologies (Hiring for client); Navi Mumbai; Hybrid; INR 4,000,000 - 7,000,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Nxtwave Disruptive Technologies is hiring a senior Cloud Data Architect to lead solution design and delivery for client data platforms. You will own discovery, guide data engineering teams, and ensure secure, scalable architectures across cloud data warehouses and data lakes.

Role requires hands-on data engineering skills with DevOps familiarity, strong communication, and experience consulting international clients. Hybrid work in India may apply.

Qualifications

• Expertise in Snowflake and other cloud data warehouses (Azure SQL DW, BigQuery).
• Strong knowledge of Data Lake and Data Warehouse architecture across GCP and Azure.
• Experience with data integration/ingestion frameworks using Python, Airflow, Azure Data Pipelines.
• Experience with cloud data warehouse, data lake, migration and digital transformation projects (2–3 large projects).
• Knowledge of structured, semi-structured and unstructured data and various ingestion methods.
• Hands-on with DevOps tools Git and Docker; awareness of DataOps in Agile SDLC.
• Experience consulting UK/US clients.

Responsibilities

• Solution design and innovation with senior architects and CTOs.
• Discovery ownership: requirements analysis, feasibility, GAP analysis.
• Technical build: guide development teams on data projects.
• Leadership: mentor team and align with CXO priorities.
• Communication: present to stakeholders and track project status.
• Delivery ownership: end-to-end development responsibility.
• Quality accountability: ensure robust, secure architectures and testing.
• Cloud and data engineering leadership across distributed pipelines, modelling and security.

Skills

Cloud data architecture

Data modeling

Data integration

Technical leadership

Mentoring

Stakeholder communication

Consulting experience

DataOps mindset

Tools

Python

Airflow

Azure Data Pipelines

Git

Docker

Snowflake

BigQuery

Job description

1. Solution Design and Innovation: Work closely with Senior Solution Architects and CTOs to advise on and select optimal technologies, keeping up with emerging trends and pushing for best practices and innovation. Present solutions to client Enterprise Architects to influence and secure agreement.
2. Discovery Ownership: Own requirement analysis, feasibility studies and GAP analysis during the discovery phase. Break down complex business requirements into workable technical solutions.
3. Technical Build: Deliver the technical solution recommended during solution consulting by working with development and technology teams. Guide and mentor the core development team on data projects.
4. Leadership: Manage the team and guide the organisation on new technology during onboarding. Support the Project Manager on effort estimation, cost and risk impact analysis. Mentor and coach technical team members. Work on projects aligned with CxO priorities.
5. Communication: Deliver technical presentations and discovery walkthroughs, provide status updates to key stakeholders, and communicate effectively with both technical teams and non-technical business stakeholders.
6. Delivery Ownership: Take end-to-end development and delivery responsibility, working closely with Delivery and Project Managers to ensure successful outcomes.
7. Quality Accountability: Ensure architectures are robust, maintainable and secure. Establish best practices for data security and compliance, and ensure quality control and testing.
8. Cloud and Data Engineering Leadership: Provide hands‑on technical leadership across distributed data processing, real‑time and batch data pipelines, data modelling and optimisation, and security and regulatory standards.

Desired Candidate Profile:

1. Expertise in Snowflake and other cloud data warehouses, including Azure SQL DW and Google BigQuery. Strong implementation knowledge of Data Lake and Data Warehouse architecture across GCP and Azure.
2. Experience with integration and ingestion frameworks using Python, Airflow, Azure Data Pipelines or similar tools. Big data experience is not required.
3. Experience working on cloud data warehouse, data lake, migration and digital transformation projects, with at least 2 to 3 large projects involving cloud services.
4. Strong knowledge of structured, semi-structured and unstructured data, with experience in stream, API, file and microservice based data ingestion.
5. Understanding of data structure and modelling principles, with the ability to add value during data unification and modelling.
6. Hands‑on experience with the data engineering stack, including DevOps tools such as Git and Docker, security stack implementation, and awareness of DataOps principles within an Agile SDLC.
7. Snowflake experience is an added advantage.
8. Excellent communication skills, with the ability to explain complex technical ideas to both technical and non-technical stakeholders.
9. Ability to lead architectural decisions, drive best practices and mentor team members.
10. Experience in consulting, primarily with UK and US clients.

Nice to Have:

1. Certifications such as Google Cloud Certified Professional Cloud Architect or Data Engineer.
2. Experience with hybrid or on‑premise plus cloud environments.
3. Knowledge of compliance frameworks relevant to the market, such as GDPR or HIPAA.
4. Prior experience in enterprise consulting or professional services.
5. Experience scaling global cloud teams or working with globally distributed systems.