Posted:1 week ago|
Platform:
On-site
Full Time
Responsibilities
Design and implement scalable data pipelines and ETL processes using Azure Data Factory, Databricks, and other Azure services.
Develop and optimize data storage solutions, including Azure Data Lake, Azure SQL Database, ADF, Snowflake, SQL and Pyspark.
Collaborate with stakeholders to understand business requirements and translate them into technical solutions.
Ensure data quality, security, and compliance by implementing best practices for governance and monitoring.
Perform performance tuning and optimization of data workflows and queries.
Create documentation for data architecture, processes, and workflows to ensure knowledge sharing across teams.
Work closely with analytics teams to enable advanced reporting and machine learning capabilities.
Qualifications we seek in you
Minimum Qualifications
Bachelor's degree in computer science, Information Technology, or a related field.
Strong experience working in Azure data services, data engineering & transformation projects.
Strong understanding of data warehousing, ETL processes, OLAP concepts and data modelling concepts
Strong communication and collaboration abilities.
Experience on Agile way of working
Mandatory Skills:
Proficiency in Azure services such as Azure Data Factory, Azure Data Lake and Databricks.
Strong programming skills in Pyspark, SQL for data processing and transformation.
Experience with ETL/ELT processes and designing data pipelines.
Experience in Snowflake
Knowledge of cloud architecture principles and best practices for scalability and security.
Familiarity with CI/CD pipelines and DevOps practices for deploying data solutions.
Preferred Qualifications/ Skills
Experience in Banking projects using Azure.
Certification in Microsoft Azure (such as Azure Data Engineer Associate).
Understanding of Power BI or other visualization tools for reporting purposes.
Strong problem-solving skills and ability to work in a fast-paced environment.
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