Azure Data Engineer
23 hours ago
Responsibilities :
- Developing Modern Data Warehouse solutions using Databricks and Azure Stack.
- Ability to provide solutions that are forward-thinking in the data engineering and analytics space.
- Collaborate with DW/BI leads to understanding new ETL pipeline development requirements.
- Triage issues to find gaps in existing pipelines and fix the issues.
- Work with businesses to understand the need in the reporting layer and develop a data model to fulfill reporting needs.
- Help joiner team members to resolve issues and technical challenges.
- Drive technical discussions with client architects and team members.
- Orchestrate the data pipelines in the scheduler via Airflow.
Requirements :
- Must have a total of 5 years of IT experience in Data warehouse/ETL projects.
- Deep understanding of Star and Snowflake dimensional modeling.
- Strong knowledge of Data Management principles.
- Good understanding of Databricks Data & AI platform and Azure Data Factory Architecture OR ADF.
- Should have hands-on experience in SQL, Python, and Spark (PySpark).
- Candidate must have experience in Azure stack.
- Desirable to have ETL with batch and streaming (Kinesis).
- Experience in building ETL / data warehouse transformation processes.
- Experience working with structured and unstructured data including imaging & geospatial data.
- Experience working in a Dev/Ops environment with tools such as Terraform, CircleCI, and GIT.
- Proficiency in RDBMS, complex SQL, PL/SQL, Unix Shell Scripting, performance tuning, and troubleshooting.
- Databricks Certified Data Engineer Associate/Professional Certification (Desirable).
- Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects.
- Should have experience working in Agile methodology.
- Strong verbal and written communication skills.
- Strong analytical and problem-solving skills with high attention to detail.
- Mandatory Skills: Python/ PySpark / Spark with Azure/Azure Data Factory
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