Experience: 8+ years IT experience, with at least 5+ years of “Quality Engineer” focused titles/roles,
Data Tools: Hands on experience with Apache Beam or Informatica.
Testing: Hands on experience with automated testing activities/outcomes
DevOps: Experience with the processes involving Microservices facilities for artefacts developed
Platform/OS: Mid-range/Unix
Languages: Unix (Shell) Scripting/commands, SQL, Python
File formats: Text, CSV, Parquet, JSON, XML
Scheduling: Jenkins, Airflow
Auto Scripting: Designing/creation of scripts for repetitive activity. E.g. Unix scripting/SQL
Big data: Exposure to Data Lake Concepts, Hive (Schema), HDFS
Source Control tools: GIT
Delivery Models: Agile, Scrum
Ingestion Design: Create/assess Source/Target data mapping designs
Frameworks: Development and delivery frameworks
Activity Reporting/Repository: Jira, Confluence.
Quality: Accuracy and attention to detail Nice to have:
Industry: Financial Services/Banking
Solutions: Define solutions from High level to detail design to address automating ingestion activity. Facilitate/confirm requirements from product owners, business team members and technical associates,
Process Automation: Automating processes in file management, testing data in files, analysis and design, configuration management.
Script Automation: Ability to design/create scripts to automate/improve data copy/migration/ETL for any repetitive activity.
Languages: Java, Python
Scheduling: Control-M
Databases: Relational. E.g. POSTGRESS, Oracle - as a ETL developer
File Formats: Mainframe – experience with referencing its data formats/copybooks
Big data: Experience referencing/using Hive (Schema) to access data in HDFS
Metadata management tools: MDM, EDC and Axon
Performance: Assess, recommend, improve mappings, SQL queries, Batch feeds
Automation Tools: Other tools that may add value to an automation program and generally support development. E.g. API, REST, JDBC, Webservices, Message Queues/Load balancer,
Cloud: Experience with processing of data files to be ingested/stored in the Cloud, preferably with AWS.
Prod Support: Experience in a production support role performing root cause / impact analysis - under time constraints