Principal Architect

About the Company

• Tiger Analytics is a global AI and analytics consulting firm. With data and technology at the core of our solutions, our 2800+ tribe is solving problems that eventually impact the lives of millions globally. Our culture is modeled around expertise and respect with a team-first mindset. Headquartered in Silicon Valley, youʼll find our delivery centers across the globe and offices in multiple cities across India, the US, the UK, Canada, and Singapore, including a substantial remote global workforce. Weʼre Great Place to Work-Certified™.

About the Role

Responsibilities

Work as a principal advisor on data architecture, across various data requirements, aggregation – data lake – data models – data warehouse etc.

Lead cross-functional teams, define data strategies, and leverage the latest technologies in data handling. Define and govern data architecture principles, standards, and best practices to ensure consistency, scalability, and security of data assets across projects.

Suggest best modelling approach to the client based on their requirement and target architecture. Analyze and understand the Datasets and guide the team in creating Source to Target Mapping and Data Dictionaries, capturing all relevant details.

Profile the Data sets to generate relevant insights. Optimize the Data Models and work with the Data Engineers to define the Ingestion logic, ingestion frequency and data consumption patterns.

Establish data governance practices, including data quality, metadata management, and data lineage, to ensure data accuracy, reliability, and compliance.

Drives automation in modeling activities Collaborate with Business Stakeholders, Data Owners, Business Analysts, Architects to design and develop next generation data platform.

Closely monitor the Project progress and provide regular updates to the leadership teams on the milestones, impediments etc.

Guide / mentor team members, and review artifacts.

Contribute to the overall data strategy and roadmaps.

Propose and execute technical assessments, proofs of concept to promote innovation in the data space.

Required Skills

Minimum 16 years of experience Deep understanding of data architecture principles, data modelling, data integration, data governance, and data management technologies.

Experience in Data strategies and developing logical and physical data models on RDBMS, NoSQL, and Cloud native databases.

Decent experience in one or more RDBMS systems (such as Oracle, DB2, SQL Server)

Good understanding of Relational, Dimensional, Data Vault Modelling.

Experience in implementing 2 or more data models in a database with data security and access controls.

Good experience in OLTP and OLAP systems

Excellent Data Analysis skills with demonstrable knowledge on standard datasets and sources.

Good Experience on one or more Cloud DW (e.g. Snowflake, Redshift, Synapse)

Experience on one or more cloud platforms (e.g. AWS, Azure, GCP)

Understanding of DevOps processes

Hands-on experience in one or more Data Modelling Tools

Good understanding of one or more ETL tool and data ingestion frameworks

Understanding of Data Quality and Data Governance

Good understanding of NoSQL Database and modeling techniques

Good understanding of one or more Business Domains

Understanding of Big Data ecosystem

Understanding of Industry Data Models

Hands-on experience in Python

Experience in leading the large and complex teams

Good understanding of agile methodology