ETL Data Architect

Role Overview

We are seeking a highly skilled ETL Data Architect with 812 years of experience to lead our data architecture, engineering, and analytics initiatives as part of the Digital Transformation (DT) Data Practice. The ideal candidate will be responsible for designing scalable data platforms, modern ETL/ELT pipelines, cloud-based data solutions, BI/Analytics ecosystems, and DataOps. This role demands strong technical leadership, strategic thinking, and deep expertise across the end-to-end data lifecycle management.

Key Responsibilities

• Architect scalable data platforms including Data Lakes, Data Warehouses, and Lakehouse solutions across Azure, AWS, or GCP.
• Define data modeling standards, optimization practices, and governance guidelines for enterprise data platforms.
• Lead architectural decisions across data ingestion, transformation, storage, quality assurance, and consumption layers.
• Design and implement high-performance ETL/ELT pipelines
• Build scalable batch and real-time ingestion frameworks
• Ensure strong data quality, lineage tracking, and metadata management across all data flows.
• Implement CI/CD pipelines and modern DataOps practices to streamline development and deployment.
• Automate pipeline monitoring, alerting, logging, testing, and orchestration for operational efficiency.
• Build and optimize analytical data models and consumption layers for BI platforms such as Power BI, Tableau, Qlik, and Looker.
• Collaborate with business teams, cloud architects, data scientists, and application teams to deliver cohesive data solutions.
• Provide technical leadership to engineering teams on design, architecture, and performance tuning activities.
• Establish and enforce enterprise data quality, governance, and security frameworks.
• Participate in presales activities, including solutioning, proposal creation, and customer presentations.

Key Skills & Competencies

Technical Skills

• Strong hands-on experience in ETL/ELT tools: Informatica, SSIS, ADF, Glue, DBT etc.
• Expertise in designing data lakes, DWH, Lakehouse architectures.
• Proficiency in SQL, Python, Spark, PySpark.
• Experienced in cloud platforms: Azure (preferred), AWS, or GCP.
• Strong knowledge of databases: SQL Server, Oracle, Snowflake, BigQuery, Redshift, Synapse, Databricks.
• Solid understanding of data modeling (3NF, Star/Snowflake schema, Data Vault).
• Experience with streaming technologies: Kafka, EventHub, Kinesis, PubSub.
• Familiarity with DataOps practices: CI/CD, Git, testing automation, monitoring.
• Good understanding of data security, compliance, IAM, and governance.

Soft Skills

• Strong communication and stakeholder management skills.
• Ability to lead end-to-end solution design discussions with technical and business leaders.
• Strong analytical and problem-solving skills.
• Ability to work in agile, fast-paced, cross-functional environments.

Qualifications & Experience

• Bachelor's/masters degree in engineering, Computer Science, or a related field.
• Certifications in Azure/AWS/GCP (e.g., Azure Data Engineer/Architect, AWS Data Analytics, GCP Data Engineer).
• Experience in working with GenAI-enabled data solutions or semantic modeling (optional advantage).
• Prior experience supporting Digital Transformation or Enterprise-scale data modernization programs.

Why Join Us?

• Opportunity to lead enterprise Data Transformation programs.
• Work with a growing DT Practice with modern data, AI, and cloud solutions.
• Collaborative environment with strong emphasis on innovation, reusable solutions, and capability development.
• Exposure to strategic initiatives, presales, and customer-facing solutioning.