Cloud ETL Architect

We are seeking an experienced and highly skilled Cloud ETL Architect to play a foundational leadership role within our Digital Transformation (DT) Data Practice. This role goes beyond traditional pipeline design and development. The ideal candidate will define enterprise-scale data architecture, lead hyperscaler-based solutioning, support RFPs and proposals, engage with clients, and establish strong technical governance across complex delivery programs.

Roles & Responsibilities :

Architecture & Strategy :

- Define and implement enterprise data architecture strategies aligned with business and digital transformation objectives.

- Design scalable cloud-based ETL/ELT and data integration architectures.

- Develop data modernization roadmaps, including migration from legacy/on-premise systems to cloud platforms.

- Evaluate and recommend appropriate technologies, frameworks, and architectural patterns.

- Define architecture standards, best practices, and reusable frameworks for enterprise data platforms.

Data Engineering & Cloud Platforms :

- Architect robust data ingestion, transformation, orchestration, and processing pipelines.

- Design solutions across leading cloud platforms such as AWS, Microsoft Azure, and Google Cloud Platform.

- Work with modern data technologies including data lakes, lakehouses, data warehouses, and distributed processing frameworks.

- Provide technical leadership on ETL/ELT tools, APIs, streaming platforms, and batch processing solutions.

- Ensure scalability, performance optimization, reliability, and cost efficiency across data platforms.

BI, Analytics & Semantic Layer :

- Design data architectures that support enterprise BI, advanced analytics, and reporting requirements.

- Define semantic layers, curated data models, and data consumption frameworks.

- Collaborate with analytics and business intelligence teams to ensure data platforms are optimized for reporting and decision-making.

- Support integration with visualization and BI tools such as Power BI, Tableau, Looker, or similar platforms.

Data Quality, Governance & Security :

- Define enterprise data quality frameworks, validation mechanisms, and monitoring standards.

- Implement data governance principles including metadata management, lineage, cataloging, and master data considerations.

- Ensure compliance with enterprise security standards and data privacy regulations.

- Design role-based access controls, encryption, auditing, and secure data access mechanisms.

- Establish governance frameworks for cloud data platforms and engineering practices.

Presales, RFP & Solution Ownership :

- Lead technical solutioning for RFPs, RFIs, proposals, and client presentations.

- Understand customer business challenges and translate them into scalable data architecture solutions.

- Develop solution architectures, effort estimates, implementation approaches, and technology recommendations.

- Participate in client discussions, workshops, discovery sessions, and technical presentations.

- Collaborate with sales and business teams to support opportunity qualification and solution development.

- Take ownership of technical proposals and ensure alignment between client requirements and proposed solutions.

DataOps & Delivery Governance :

- Establish DataOps practices for continuous integration, deployment, testing, and monitoring of data pipelines.

- Define standards for version control, automated testing, release management, and production support.

- Implement monitoring and observability frameworks for data pipelines and platforms.

- Drive improvements in deployment efficiency, reliability, and operational excellence.

Delivery Leadership :

- Provide technical leadership across multiple enterprise data transformation programs.

- Mentor and guide data engineers, ETL developers, architects, and technical leads.

- Conduct architecture reviews and ensure adherence to defined standards and best practices.

- Identify technical risks, dependencies, and mitigation strategies across projects.

- Collaborate with project managers, business stakeholders, and technology teams to ensure successful delivery.

- Drive continuous improvement and innovation within the Data Practice.

Required Skills & Experience :

- 10 - 15 years of overall experience in Data Engineering, ETL/ELT, Data Architecture, and Cloud Technologies.

- Strong experience in designing and implementing enterprise-scale cloud data platforms.

- Hands-on experience with at least one major cloud platform: AWS, Azure, or GCP.

- Strong expertise in ETL/ELT architecture and modern data integration frameworks.

- Experience with technologies such as Databricks, Snowflake, Azure Data Factory, AWS Glue, Informatica, Talend, or similar tools.

- Strong understanding of Data Lakes, Lakehouse architectures, Data Warehouses, and distributed data processing.

- Experience with SQL, Python, Spark, and other relevant data engineering technologies.

- Strong understanding of data governance, security, metadata management, and data quality frameworks.

- Experience in designing BI and analytics-ready data architectures.

- Mandatory experience in Presales, RFP response, proposal preparation, and client-facing solutioning.

- Experience in leading architecture discussions and technical workshops with enterprise clients.

- Strong stakeholder management and communication skills.

- Proven experience leading and mentoring technical teams.

Preferred Qualifications :

- Cloud certifications in AWS, Azure, or GCP.

- Certifications in Databricks, Snowflake, Informatica, or other relevant data technologies.

- Experience working within Digital Transformation or Data Consulting practices.

- Strong understanding of Agile and DevOps/DataOps methodologies.

- Experience in large-scale enterprise transformation and cloud migration programs.

What We Are Looking For :

The ideal candidate is a strategic thinker and hands-on technology leader who can confidently engage with clients, define enterprise data architectures, lead technical solutioning, and ensure successful program delivery. This individual should bring a strong combination of technical depth, cloud expertise, presales experience, and leadership capabilities.

Skills

Data Engineering, ETL, Data Architect, DataOps, Data Management, Python, Spark, DataLake, Snowflake DB