Note:
For Data Engineer, we're looking for a candidate who is very good in
Python, Writing code, syntax, classes, etc.
Major Responsibilities:
Building and maintaining data pipelines to ingest data from source systems into Databricks
Designing, Building and maintaining generic frameworks to ingest data through the medallion layers
Working with the core data platform team to integrate the framework with reference architecture
Assisting the data mesh teams with best practices and onboarding to the new framework
Requirements:
10+ years of data engineering experience in building OLTP and OLAP databases, both on-prem and in the cloud
5+ years of experience with large scale data processing using
SQL, Python, Pandas and Pyspark
5+ years of experience building robust and scalable data pipelines in Databricks Lakehouse platform on any key cloud platform provider, preferably Azure cloud
Experience with implementing Medallion architecture for data processing
Experience with implementing Streaming data ingestion using Kafka
Test driven development experience
Proven experience in solution design and applying best design practices
Data modelling and ER/UML diagram skills
Experience with orchestration/enterprise scheduler platforms like Airflow, Tidal etc..
Experience with implementing API based data integration pipelines
Experience with source control and DevOps for CI/CD
Experience working in Agile/scrum methodologies
Experience with Jira, confluence for project work and documentation
Experience with Service now for incident management
Finance domain knowledge in Investment Banking (Securities, Capital markets) and Security reference data knowledge
Nice to have ADF and SSIS experience
College degree required.