Solutions Office at Intellias is the team of high-end professionals with strong consulting profile. The aim of this unit on a contrary to delivery units (concentrated on certain account) is to provide solution-oriented services to our potential, new and existing customers as well as to internal company units.
We are looking for seasoned professionals with a wide range of experience willing to tackle complex technical business problems and contribute with their experience, intelligence, and inspiration to our team.
The Data Architect should have a highly developed set of analytical, communication skills and consulting capability. Also, ability to present and communicate complex technical solutions both to the client and team members. He or she should be able to identify technical risks, propose solutions and effectively communicate them to all stakeholders.
- 8+ years in Software Development;
- 2+ years in Data Architecture;
- 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 Processing/Transformation technologies, BigData Storage technologies, BigData Access technologies generally and associated with Cloud technologies specifically;
- Must be proficient with Data analysis and synthesis, Data communication, Data governance, Data modeling, Data standards, Data innovation, Metadata management, Problem resolution (data), Strategic thinking (data architecture);
- Turning business problems into data design. You can design data architecture by dealing with problems that span different business areas. You can draw links between problems in order to reach common solutions. You can work across multiple subject areas, a single large or complicated subject area;
- Have experience to transform the data as corporate resources into Enterprise with Data Driven Architecture;
- Excellent interpersonal communication skills to explain complex technical topics in an easily digestible manner;
- Experience in following technological stack would be a big advantage: Python, Spark, Kubernetes, NiFi, Kafka, Flink, Hadoop, PostgreSQL, Oracle DB, Prometheus/Grafana, Jenkins, ELK.
- Define the technological vision and lead the design of new services or new features and tools;
- 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;
- 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;
- Evaluate existing technologies and tools to determine their strengths and weaknesses and recommend those that best meet project objectives and expectations;
- Be accountable for the definition of the organization’s data strategy;
- Champion data architecture across the organization and set the standards and ways of working for the data architecture community;
- Provide advice to project teams and oversee the management of the full data product life cycle and lead the implementation of required solutions;
- Have responsibility for making sure that organizations systems are designed in accordance with the data architecture.