RQ11099 - DataOps/Cloud Data Engineer - Senior

MUST HAVES:

· Data engineering (pandas, pyspark)

· Data lakehouse solutions such as Databricks (Delta Lake).

· Working with XLSX, CSV, JSON files, relational databases, cloud storage, structured and unstructured data

· Experience using AWS Services such as Glue, StepFunctions, Lambda, S3

· Extract/Transform/Load data using tools such as Informatica IDMC

Experience and Skill Set Requirements

Data engineering Experience

• Programming & scripting: Python, SQL, Linux shell, PowerShell.
• Data manipulation/analysis using pandas and pyspark.
• Working with XLSX, CSV, JSON files, relational databases, cloud storage, structured and unstructured data

40%

Cloud experience

• AWS and/or Azure services.
• Cloud data warehouse solutions such as AWS Redshift.
• Data lakehouse solutions such as Databricks (Delta Lake).
• Data processing orchestration/automation

25%

Data Warehouse

• ETL tools (such as Azure Data Factory, AWS Glue) as well as cloud agnostic tools such as Informatica IDMC.
• Data modeling & architecture: relational and dimensional modeling.
• Data reporting/visualization.

25%

Other Skills

• Full SDLC from requirements gathering, design, implementation, testing to deployment and production support
• Project management (agile/scrum and waterfall)
• Change and Incident management
• Communication, presentation and negotiation skills
• Consulting, problem-solving and decision-making skills

5%

Public Sector

• Experience working in OPS and/or public sector in general

5%