Job
Description
As a Data Engineer with 5+ years of hands-on experience in data engineering/ETL using Databricks on AWS / Azure cloud infrastructure and functions, your role will involve: - Implementing highly performant data ingestion pipelines from multiple sources leveraging your deep understanding of data warehousing concepts such as Dimensional (star-schema), SCD2, Data Vault, Denormalized, OBT. - Utilizing your strong proficiency in Python and SQL to perform root cause analysis on internal and external data and processes, answering specific business questions, and identifying opportunities for improvement. - Leveraging your experience with AWS services like S3, Athena, Glue, Lambda to enhance data warehousing and analytics capabilities. - Utilizing your expertise in Databricks platform features like Delta Lake, Databricks SQL, MLflow for efficient data processing and analysis. - Integrating end-to-end Databricks pipelines to ensure the quality and consistency of data from source systems to target repositories. - Collaborating within an Agile delivery / DevOps methodology to deliver proof of concept and production implementation in iterative sprints. - Demonstrating basic working knowledge of API or Stream based data extraction processes like Salesforce API, Bulk API. - Applying your understanding of Data Management principles including quality, governance, security, privacy, life cycle management, and cataloguing to ensure data integrity and compliance. Qualifications required for this role include: - 5+ years of hands-on experience in data engineering/ETL using Databricks on AWS / Azure cloud infrastructure and functions. - 3+ years of experience in PBI and Data Warehousing performing root cause analysis on internal and external data and processes. - Strong proficiency in Python and SQL. - Experience with CI/CD on Databricks using tools such as BitBucket, GitHub Actions, and Databricks CLI. - Nice to have: Databricks certifications and AWS Solution Architect certification. - Nice to have: experience with building data pipelines from various business applications like Salesforce, Marketo, NetSuite, Workday, etc. This role offers the opportunity to work with cutting-edge technologies and make a significant impact on data processing and analytics within the organization. As a Data Engineer with 5+ years of hands-on experience in data engineering/ETL using Databricks on AWS / Azure cloud infrastructure and functions, your role will involve: - Implementing highly performant data ingestion pipelines from multiple sources leveraging your deep understanding of data warehousing concepts such as Dimensional (star-schema), SCD2, Data Vault, Denormalized, OBT. - Utilizing your strong proficiency in Python and SQL to perform root cause analysis on internal and external data and processes, answering specific business questions, and identifying opportunities for improvement. - Leveraging your experience with AWS services like S3, Athena, Glue, Lambda to enhance data warehousing and analytics capabilities. - Utilizing your expertise in Databricks platform features like Delta Lake, Databricks SQL, MLflow for efficient data processing and analysis. - Integrating end-to-end Databricks pipelines to ensure the quality and consistency of data from source systems to target repositories. - Collaborating within an Agile delivery / DevOps methodology to deliver proof of concept and production implementation in iterative sprints. - Demonstrating basic working knowledge of API or Stream based data extraction processes like Salesforce API, Bulk API. - Applying your understanding of Data Management principles including quality, governance, security, privacy, life cycle management, and cataloguing to ensure data integrity and compliance. Qualifications required for this role include: - 5+ years of hands-on experience in data engineering/ETL using Databricks on AWS / Azure cloud infrastructure and functions. - 3+ years of experience in PBI and Data Warehousing performing root cause analysis on internal and external data and processes. - Strong proficiency in Python and SQL. - Experience with CI/CD on Databricks using tools such as BitBucket, GitHub Actions, and Databricks CLI. - Nice to have: Databricks certifications and AWS Solution Architect certification. - Nice to have: experience with building data pipelines from various business applications like Salesforce, Marketo, NetSuite, Workday, etc. This role offers the opportunity to work with cutting-edge technologies and make a significant impact on data processing and analytics within the organization.
