Position: Technical Lead/Data Engineer  for Data Platform
Company: Intellias
Category: Data Science
Experience required: 3y
English level: upper

Team will be responsible for platform solution design and development with ambition plan to grow and onboard new teams & business hypothesis to this platform.

Project goal to implement real-time Data Platform solution with ML&AI within the following capabilities:
Core Data Platform
Onboarded Data Producer/Consumer Applications, Configuration & CustomisationsOnboarding & Management of Data Producer/Consumer Applications
Application, Data Source, Job, Job Data, Job Steps, and Data Access Taxonomies
Standardized Push/Pull Streaming Ingestion Interfaces
Standardized Push/Pull Batch Ingestion Interfaces
Polyglot Data-lake Storage (e.g., Bucket, KV, NoSQL, Search, Warehouse, SQL, etc.) and many other features.

Responsibilities:
Define the technological vision and lead the design of new services or new features and tools when current options do not meet business needs;
Determine any necessary services and tool enhancements to meet project needs and ensure the feasibility of these upgrades;
 Ensure the coherence, efficiency, scalability, modularity, and compatibility of the features developed by the team;
Analyze and resolve engineering issues pertaining to the services, tools, and/or middleware;
In collaboration with the technical directors, communicate the technical constraints of the engines and tools to team members to inform them on production options and related best practices;
Define the measures required to ensure the data engines optimal performance
Act as a point of contact for all technical issues on the data services and tools;
Manage development teams;
Anticipate technological advances, understand the issues brought about by new hardware, and implement software systems that support these changes and possibilities;
 Oversee the design of multiple data models and have a broad understanding of how each model fulfills the needs of the business from technical point of view

Requirements:
Must be proficient with DATAHUB solutions/patterns which include ODL(Operational Data Lake), ODS (Operational Data Store) and ADL(Analytic Data Lake).
Must be proficient with Clouds generally and proficiently build the Cloud-Native solutions and tools to design BigData PaaS/IaaS.
Must be proficient with BigData Ingestion technologies generally and associated with Cloud technologies specifically. 
Must be proficient with BigData Processing/Transformation technologies generally and associated with Cloud technologies specifically. 
 Must be proficient with BigData Storage technologies generally and associated with Cloud technologies specifically. 
Must be proficient with BigData Access technologies generally and associated with Cloud technologies specifically. 
Must be proficient with BigData technologies generally and associated with Cloud technologies specifically.
Data innovation. You can identify areas of innovation in data tools and techniques and recognize appropriate timing for adoption.
Microservices & API Processors; 
Query API (e.g., J/ODBC); 
Bucket, KV, NoSQL, Search, Warehouse, SQL;
experience with RBAC (Role-Based Access Controls);

Higher Education: Bachelor’s Degree or higher in IT, Applied Mathematics or similar