Transformational Business Technology Strategist

Transformative Data Architect - A Visionary Leader

About Us

A boutique AI and data engineering firm that empowers Fortune 1000 companies through AI-powered decision intelligence, especially in finance and supply chain transformation.

Key Responsibilities

1. Act as a key member of the consulting team helping clients to re-invent their corporate finance function by leveraging advanced analytics.
2. Work closely with senior stakeholders of the clients designing and implementing data strategy in finance space which includes multiple use cases viz. controllership, FP&A and GPO.
3. Develop technical solutions to deliver scalable analytical solutions leveraging cloud and big data technologies.
4. Collaborate with business consultants and product owners to design and implement technical solutions.

Technical Requirements

• Design and drive end-to-end data and analytics solution architecture from concept to delivery on Google Cloud Platform (GCP).
• Design, develop, and support conceptual, logical, and physical data models for advanced analytics and ML-driven solutions.
• Ensure integration of industry-accepted data architecture principles, standards, guidelines, and concepts with other domains, along with coordinated roll-out and adoption strategies.
• Drive the design, sizing, provisioning, and setup of GCP environments and related services such as BigQuery, Dataflow, and Cloud Storage.
• Provide mentoring and guidance on GCP-based data architecture to engineering, analytics, and business teams.
• Review solution requirements and architecture for appropriate technology selection, efficient resource utilization, and effective integration across systems and technologies.
• Advise on emerging GCP trends and services, and recommend adoption strategies to maintain competitive edge.
• Participate in pre-sales engagements, PoCs, and contribute to publishing thought leadership content.
• Collaborate closely with the founders and leadership team to shape and drive the organization's cloud and data strategy.

Qualifications

• Demonstrated experience in delivering multiple data and analytics solutions on GCP.
• Hands-on experience with data ingestion, processing, and orchestration tools such as Dataflow, Pub/Sub, Dataproc, Cloud Composer, and Data Fusion.
• Deep expertise with GCP data warehousing and analytics services including BigQuery, Cloud Storage, and Looker.
• Familiar with Data Mesh, Data Fabric, and Data products, Data Contracts, and experience in data mesh implementation.
• Strong understanding and practical experience with different data modeling techniques - relational, star, snowflake, DataVault, etc., and working with transactional, time-series, and unstructured datasets.
• Experience with enterprise data management i.e. data quality, metadata management, data governance, data observability using GCP-native or third-party tools.
• Experience in design and implementation of event-driven architecture and tools like Google Pub/Sub or Kafka will be an added advantage.
• Familiar with AI, GenAI concepts, and Vertex AI. Solid grasp of operational dependencies and integration across applications, networks, security, and infrastructure in the cloud - including IAM, VPCs, VPNs, firewall rules, GKE, and service accounts.
• Strong foundation in computer science or software engineering, with expertise in software development methodologies and Dev/Data Ops and CI/CD.
• Practical experience using tools such as Terraform, Cloud Build, GitHub Actions, and scripting via Python, Bash, etc.
• Familiar with software development lifecycle and cloud-native application development.
• Remains hands-on with technology and stays current with industry trends and GCP service evolution.
• Demonstrated hands-on experience coding in Python, SQL, and Spark, with the flexibility to pick up new languages or technologies quick.
• GCP professional data engineer certification will be an added advantage.