- Data Pipeline : Develop and maintain scalable data pipelines and builds out new API integrations to support continuing increases in data volume and complexity

- Data Integration : Connect offline and online data to continuously improve overall understanding of customer behavior and journeys for personalization. Data pre-processing including collecting, parsing, managing, analyzing and visualizing large sets of data

- Data Quality Management : Cleanse the data and improve data quality and readiness for analysis. Drive standards, define and implement/improve data governance strategies and enforce best practices to scale data analysis across platforms

- Data Transformation : Processes data by cleansing data and transforming them to proper storage structure for the purpose of querying and analysis using ETL and ELT process

- Data Enablement : Ensure data is accessible and useable to wider enterprise to enable a deeper and more timely understanding of operation.

Qualifications & Specifications :

- Masters /Bachelors degree in Engineering /Computer Science/ Math/ Statistics or equivalent.

- Strong programming skills in Python/Pyspark/SAS.

- Proven experience with large data sets and related technologies Hadoop, Hive, Distributed computing systems, Spark optimization.

- Experience on cloud platforms (preferably Azure) and it's services Azure Data Factory (ADF), ADLS Storage, Azure DevOps.

- Hands-on experience on Databricks, Delta Lake, Workflows.

- Should have knowledge of DevOps process and tools like Docker, CI/CD, Kubernetes, Terraform, Octopus.

- Hands-on experience with SQL and data modeling to support the organization's data storage and analysis needs.

The job is for:

Women candidates preferred