Tiger Analytics

Tiger Analytics

Tiger Analytics is a leading advanced analytics consulting firm partnering with Fortune 100 companies to drive business value through expertise in marketing science, customer analytics, and operations analytics.

Professional Services
1K-5K
Founded 2011

Description

  • Lead enterprise data and analytics architecture engagements using AWS and Databricks aligned to business goals.
  • Assess legacy data environments and define target-state architectures, modernization roadmaps, migration strategies, and technology blueprints.
  • Advise senior client stakeholders through architecture workshops, technical discovery sessions, and strategic consulting engagements.
  • Design end-to-end cloud data platform solutions across data lakes, lakehouses, data warehouses, streaming, metadata, governance, and analytics ecosystems.
  • Define architecture standards, reusable design patterns, best practices, and governance frameworks.
  • Lead solutioning discussions with clients, implementation partners, and cross-functional delivery teams to ensure consistent architecture execution.
  • Design scalable data ingestion, transformation, storage, and analytics architectures for structured, semi-structured, and unstructured data.
  • Collaborate with business, product, engineering, and data science teams to translate requirements into technical solutions.
  • Provide architectural oversight during delivery, review technical designs, resolve complex issues, and mentor global engineering teams.
  • Support proposal development, solution estimates, RFP responses, technical presentations, and executive client discussions.

Requirements

  • 18+ years of IT experience, including at least 10 years in enterprise data and analytics architecture.
  • Strong expertise in AWS Cloud services such as S3, Glue, EMR, Lambda, Redshift, Athena, IAM, Lake Formation, Step Functions, CloudWatch, EventBridge, ECS, and EKS.
  • Extensive hands-on experience with Databricks, Delta Lake, Unity Catalog, Spark, PySpark, and lakehouse architecture.
  • Strong understanding of enterprise data warehouse, data lake, and lakehouse architectures.
  • Expertise in modern data engineering principles, ETL/ELT frameworks, metadata management, data governance, and master data management.
  • Strong knowledge of SQL, distributed data processing, cloud-native architecture patterns, and scalable data platform design.
  • Experience designing enterprise integration architectures using APIs, streaming technologies, messaging systems, and event-driven architectures.
  • Deep understanding of cloud migration strategies, modernization approaches, and hybrid architecture patterns.
  • Strong stakeholder management experience with direct interaction at executive leadership level.
  • Excellent consulting, advisory, presentation, and communication skills.

Benefits

  • Significant career development opportunities as the company grows.
  • Opportunity to work in a small, fast-growing, entrepreneurial environment.
  • High degree of individual responsibility and ownership.
  • Equal employment opportunity regardless of protected characteristics.

Interested in this position?

Apply directly on the company website

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