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The Role:

We are looking for passionate and seasoned data architects to build next generation data warehouses / data lakes and business intelligence solutions for our business stakeholders. The candidate would be required to understand and gather the data warehouse / data lake requirements, architect, design / model and implement timely solutions for the business needs. The candidate should be able to own and be responsible for the complete architecture of the solution.

Data architect will own, optimize and maintain conceptual, logical and physical data models. Exposure to Sales / Finance, Manufacturing, Quality, Engineering, Supply Chain, Finance, After-sales / Credit and Digital workplace Domain would be preferred.

Responsibilities:

The primary responsibilities of the solution architect include:

Own and drive the architecture for a project / product.
design, modify, and test technical architecture.
Continually research the current and emerging technologies and propose changes where needed
Choose the right architecture that would solve the business problems
Assess the business impact that certain technical choices have.
Provide updates to stakeholders on product development processes, costs and budgets.
Lead a team of technical people, mentor and guide them during the solution
Communicate and translate the technical solution to the team and other stakeholders
Drive re-use initiatives and promote re-use culture within the team
Design and implement various components of data pipeline that include data integration, storage, processing and analysis of business data
Analyze business requirements and derive conceptual model by identifying entities and the relationship between them. Identify attributes and create logical and physical models
Business process modelling, process flow modeling, data flow modelling skills preferable
Proficient in creating flowcharts, process flows and data flow diagrams
Collaborate with application development and support teams on various IT projects
Develop complex modules and proof of concepts
Lead and drive performance optimization efforts
Define standards and guidelines for the project and ensure team is following those
Assist in setting strategic direction for database, infrastructure and technology through necessary research and development activities
Automation should be a key driver and the development & testing should be automated through frameworks / tools
Monitoring performance and advising any necessary infrastructure changes through capacity planning & sizing exercises
Work with various vendors like cloud providers and consultants to deliver the project
Define non functional requirements and make sure that the solution adhere to the requirements
Define best practices of agile & DevOps while implementing solutions

Skills and Qualifications:

The ideal candidate should have worked on end-to-end data warehousing / data lake and / or business intelligence solutions in the past. The candidate should have the following skills sets:

Excellent understanding of distributed computing paradigm
Should have excellent knowledge in data warehouse / data lake technology and business intelligence concepts
Should have in depth understanding of coding languages like Java, Python, Scala, SQL etc.
Should have good knowledge in Relational, No-SQL, Big Data Databases and should be able to write queries
Should have strong implementation experience in all the below technology areas (breadth) and deep technical expertise in some of the below technologies:
Data integration – ETL tools like Glue, Talend and Informatica. Ingestion mechanism like Flume & Kafka
Front End/ Backend technologies: Sprintboot, React Js, Angular Js etc.
Data modelling – Dimensional & transactional modelling using RDBMS, NO-SQL and Big Data technologies. Experience in Snowflake modelling would be an advantage
Data visualization – Tools like Tableau
Master data management (MDM) – Concepts and expertise in tools like Informatica & Talend MDM
Big data – Hadoop eco-system, Distributions like Cloudera / Hortonworks, Pig and HIVE
Data processing frameworks – Spark & Spark streaming
Hands-on experience with multiple databases like PostgreSQL, Snowflake, Oracle, MS SQL Server, NOSQL (HBase / Cassandra, MongoDB), is required.
Exposure to multiple AWS components like Lambda, EC2, SNS, SES, Cloud Watch, RDS etc.
Knowledge of various data modelling techniques and should be hands on with data modelling tools like ERWin, TOAD, PowerDesigner, etc are preferable
Experience in cloud data eco-system, specifically with AWS. Experience in AWS data components like S3, Redshift & RDS, managed services like Aurora & Athena are desirable
Demonstrate strong analytical and problem solving capability
Good understanding of the data eco-system, both current and future data trends
10+ years of experience in the Solution Architect space with at least few complex & high volume data projects as an architect is mandatory