Data Analyst / Data Engineer

Job description

Mandatory skills

Data Lake, Synapse, PySpark

Responsibilities

Data Analyst / Data Engineer

Utilizes software engineering principles to deploy and maintain fully automated data transformation pipelines that combine a large variety of storage and computation technologies to handle a distribution of data types and volumes in support of data architecture design. An Data Analyst and develop data pipelines that are resilient to change, modular, flexible, scalable, reusable, and cost effective. The expectation for this role is 5-8 years of relevant experience.

Key responsibilities

• Design, develop, and maintain data pipelines and ETL processes using Microsoft Azure services (e.g., Azure Data Factory, Azure Synapse, Azure Databricks, Azure Fabric).
• Utilize Azure data storage accounts for organizing and maintaining data pipeline outputs. (e.g., Azure Data Lake Storage Gen 2 & Azure Blob storage).
• Experience in utilizing SQL DML to query modern RDBMS in an efficient manner (e.g., SQL Server, PostgreSQL).
• Good Hands-on in PowerApps, Power Automate, Power BI.
• Knowledge of REST-API, OAuth.
• Collaborate with data architects and other stakeholders to understand data requirements and deliver high-quality data solutions.
• Optimize data pipelines in the Azure environment for performance, scalability, and reliability.
• Ensure data quality and integrity through data validation techniques and frameworks.
• Monitor and troubleshoot data pipeline issues to ensure timely resolution.
• Stay current with industry trends and emerging technologies to ensure our data solutions remain cutting-edge.
• Manage the CI/CD process for deploying and maintaining data solutions.
• Good to have knowledge of any programming language like C#, Java, JavaScript, Python etc.

Required Qualifications

• Bachelor's degree in computer science, Engineering, or a related field (or equivalent experience).
• 3-5 years of proven experience as a Data Engineer or similar role dealing with data and ETL processes.
• Strong knowledge of Microsoft Azure services, including Azure Data Factory, Azure Synapse, Azure Databricks, Azure Blob Storage and Azure Data Lake Gen 2.
• Experience utilizing SQL DML to query modern RDBMS in an efficient manner (e.g., SQL Server, PostgreSQL).
• Strong understanding of Software Engineering principles and how they apply to Data Engineering (e.g., CI/CD, version control, testing).
• Strong knowledge of pyspark.
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.

Preferred Qualifications

• Learning agility
• Experience efficiently querying API endpoints as a data source.
• Understanding of the Azure environment and related services such as subscriptions, resource groups, etc.
• Understanding of Git workflows in software development.
• Using Azure DevOps pipeline and repositories to deploy and maintain solutions.
• Understanding of Ansible and how to use it in Azure DevOps pipelines.