Technical
Data Engineering
language and frameworks: Map-Reduce, Hadoop, Hive, HBase,
Elastic, AWS Kinesis, Apache Kafka, Goggle BigQuery, Amazon Redshift,
AWS Lambda, Dataflow, Cloud Functions, Snowflake, SQL
design: data-as-product, data-governance, all aspects of data
lifecycle (ingest, ETL, scrubbing, packaging as product, access and support)
sync and async data architecture, data-lakes, data-warehouses, data analytics and development of
KPI and metrics, data-modeling, mapreduce and no sql document architecture,
building async data pipeline with streams (kafka, kinesis) and serverless technology,
database optimization.
Application Engineering
languages and frameworks: .NET Desktop using C# (.net, .net-core, WPF, XAML),
.NET web using C# and VB.NET (ASP, ASP.net, .net core), Java web development using
spring and springboot, PHP (symfony and laravel), python (Django)
patterns and standards: SOA, microservices (six-sigma), MVC, MVVM, async distributed
architecture, and all GoF patterns, testing (unit, integration, end-to-end), observability,
operational excellence, engineering excellence and code quality.
Managerial
People Management
Hiring, Coaching, Mentorship, Building High-Functioning Teams
Product Management and Project Planning
OKR Based Planning, Jobs to be Done Based Planning, Capacity Planning, Solution Discovery based on Product Strategy,
Execution Plans, Reporting
Software Development Process Management
Agile Software Development (scrum and kanban), Operational Excellence, Engineering Excellence,
maintaining code standard, documentation
