• Bachelor Degree or Post Graduate in Computer Science, or relevant work experience
• 8 years of experience in an Engineering / Data ingestion and process heavy organization
• 2+ years of experience as a Data Analysis and Data Design responsible for data architecture of a SaaS application
• Experience in understanding and designing of data pipelines for ingestion and transformation, data sharding in a distributed database
• Some Hands-on experience in software development and system administration
• Knowledge of strategic IT solutions
• Familiarity with programming languages like Java or Python or PySpark
• Familiarity with Linux OS and Windows alike
• Experience in cloud computing and cloud Technologies (AWS, GCP, Azure)
• Excellent communication skills – you should be adept at listening to, understanding, and explaining key concepts to managerial and technical resources
• Good Anticipation and problem-solving skills
• Ability to prioritize and manage time – responsible for multiple streams of work at the same time
• Relationship building - Ability to form a good rapport with internal and external stakeholders
• In-depth knowledge about quality standards and security best practices

Desirable

• This person will assist in driving technology innovation for engineering projects and work on architecture of AWS, Data Lake (Databricks/Elastic) and Kubernetes
• They will also work closely with the Technology Architect to create and drive the Architecture Review Board
• Determine internal / external customer data needs and identify system specifications
• Analyze the needs of large systems and breaking them down into smaller manageable parts
• Responsible for designing the journey of data from various sources to the database and everything in between
• Plan and design the structure of data, brainstorm with team
• Analyze best technology products and systems for internal teams
• Help provide build vs buy decisions on data architecture
• Communicate data requirements to engineers; explain data architecture to them and aid throughout SDLC
• Choose / maintain suitable software, hardware and integration methods
• Assist security analysts in creating SIEM rules
• Help resolve technical problems as and when they arise
• Review testing procedures to ensure data performant and error free
• Ensure that database satisfy quality standards and procedures. Setup such standards
• Work with senior IT personnel to devise plans for future IT requirements of the organization
• Produce progress reports on key infrastructures – Databricks, Elastic and Data Pipelines