Job Title

Organization:- Leading Global Management Consulting OrganizationRole :- Senior Manager - DE(Data Architect)Experience :- 10+ YearsWhat You'll DoBe part of a Data Platform Engineering team building a unified data platform architecture to unlock the company’s internal Data and AI needs. As Senior Manager – Data Warehouse Platforms (Data Platforms Engineer)you will be an integral Individual contributor of an Agile platform team responsible for designing, delivering and running the enterprise data platforms (Snowflake & Google BigQuery) and the supporting ingestion, transformation,orchestration and governance stack. What You'll Bring8+ years in Platform engineering / Data platform roles, with 3+ years in a senior/lead (Manager / Senior Manager)capacity.Strong cloud & infra skills: Terraform, IAM, networking, logging/monitoring and FinOps for data workloads.Hands-on delivery of enterprise-scale data platforms (Snowflake and/or Google BigQuery Or Data Bricks) supporting analytics/ML at multi-TB scale.Leads data architecture design and governance, defining end-to-end scalable, secure, and resilient data architectures (batch and real-time) that support enterprise analytics.Proven expertise with ingestion and integration tools: Fivetran, AWS Glue or equivalent, and experience building secure custom connectors.Deep practical experience in dbt (models, testing, CI/CD), Airflow (DAG design, scheduling, SLAs) and SQL/Python development.Demonstrates strong leadership and business acumen by partnering with product, analytics, and business stakeholders to translate strategic objectives into scalable data platform capabilities, prioritizing initiatives based on business impact, cost efficiency, and long-term value creationOperational experience with Informatica IDMC / Catalog / Data Quality (or equivalent) for metadata, lineage and enterprise data quality.Experience deploying/operating data observability tooling (e.g., Monte Carlo) and implementing runbook-driven incident management.Demonstrated capability in security & governance: RBAC, masking/tokenization, SSO (Okta), secrets management and audit logging.Track record of platform ownership: performance tuning, capacity planning, upgrades/migrations and vendor management.Bachelor’s degree in Computer Science, Engineering or related field (Master’s preferred).Comfortable mentoring engineers, leading cross-functional teams and driving platform strategy and delivery.Relevant certifications (SnowPro, GCP Data Engineer, AWS Professional) are a plus.Additional infoYOU’RE GOOD AT: Architecting modern data platforms: Lead design, build and run of enterprise Data Warehouse platforms (Snowflake & Google BigQuery) and modern ELT tooling to enable Analytics and AI use cases. You have experience managing and setting up these platforms as an AdministratorEnabling AI through data excellence — You understand what high-quality, well-governed data means for AI.You build the framework and tooling for data pipelines and data products that power model training,inference, and continuous learning. Being a guide for Ingestion tooling implementations: Help guide customers towards right platform-based solutionsand partner with them in building appropriate connectors for batch & streaming.Owning the transformation layer with dbt,: modeling standards, testing, CI/CD and deployment governance. Build and maintain orchestration (Apache Airflow): scalable DAGs, scheduling, SLAs and alerting.Supporting Data Governance Initiatives with Platforms and Solutions: Implement enterprise data quality, cataloguing and lineage using Informatica IDMC / Catalog / Data Quality Deploying and operate data observability (e.g., MonteCarlo) and embed alerting/SLA workflows and runbooks.Solving complex engineering challenges — You bring structure and innovation to ambiguous technical problems,leveraging automation, CI/CD, and infrastructure-as-code to drive reliability and velocity. Drive automation for release management, version control, infrastructure provisioning (Terraform), and environment promotion.Defining and enforcing platform standards: schema design, partitioning/clustering, performance tuning and costcontrols (FinOps).Governance and FinOps mindset — You understand how to balance control, cost, and agility — driving data security, compliance, and platform efficiency through metrics and continuous improvement. Implement security and governance: RBAC, data masking/tokenization, audit logging, SSO (Okta), and secrets management.Hands-on technical delivery — You’re comfortable getting into code and configurations (Django, Python, dbt,Terraform, Airflow, etc.) while mentoring engineers to build sustainable, production-grade solutions.Lead incident management, capacity planning, performance tuning and platform upgrades/migrations.Manage vendor relationships, licensing, and procurement for core platform technologies.Drafting Architecture diagrams to support data problems after understanding the use case and the technical ecosystemStaying ahead of the curve — You are curious about emerging technologies (AI, Knowledge Graphs, MLOps, observability, and data contracts) and know when to pragmatically adopt them.Communicating for impact — You can explain architecture trade-offs clearly to executives, engineers, and analysts — inspiring trust and alignment through clarity and empathy.Coaching and mentoring engineers; translate business needs into measurable platform deliverables and KPIs.