Job
Description
What You'll Do Data Analytics & Modeling : Apply strong Data Analytics and Analytical Skills to understand complex business requirements and translate them into effective Data Modeling solutions. Data Pipeline Development : Design, develop, and maintain robust ETL (Extract, Transform, Load) pipelines using Azure Data Engineering services to ingest, process, and transform large datasets. Data Warehousing : Build and optimize fact and dimension tables within analytical databases, contributing to scalable data warehousing solutions. Azure Data Engineering : Hands-on development using Azure Data Engineering tools such as Azure Data Factory (ADF), Databricks, and Fabric. Programming for Data : Utilize expertise in PySpark and Python to develop and maintain efficient data processing solutions, ensuring data integrity, performance, and scalability. BI Dashboarding : Develop and maintain compelling Business Intelligence (BI) dashboards using tools like PowerBI and/or Tableau, turning raw data into actionable insights. Analytical Databases : Work with analytical databases such as Snowflake, Azure Synapse, and others to store and process large volumes of data. SQL & Programming : Demonstrate proficiency in SQL for data manipulation and querying, and possess skills in other relevant programming languages. Performance & Integrity : Ensure data integrity, quality, and optimal performance of data pipelines and BI solutions. Collaboration : Collaborate effectively with data scientists, business analysts, product managers, and other engineering teams to understand data needs and deliver comprehensive Skills & Qualifications : Experience : Minimum 2 years of core, hands-on experience in Azure Data Engineering and Business Intelligence (PowerBI and/or Tableau). Data Fundamentals : Strong understanding of Data Analytics, Analytical Skills, Data Analysis, Data Management, and Data Modeling concepts. Azure Data Engineering : Mandatory hands-on experience with Azure Data Engineering services including ADF, Databricks, and Fabric. Programming for Data : Proficiency in PySpark and Python, with a proven ability to develop and maintain robust data processing solutions. SQL Expertise : Strong proficiency in SQL for complex data querying and manipulation. BI Tools : Practical experience building BI dashboards using PowerBI and/or Tableau. Analytical Databases : Experience with analytical databases like Snowflake, Azure Synapse, etc. Problem Solving : Strong problem-solving and critical thinking abilities to tackle complex data challenges. Education : Bachelor's degree in Computer Science, Information Systems, or a related Qualifications (Nice-to-Have) : Relevant Microsoft Azure certifications (e.g., Azure Data Engineer Associate, Azure Data Analyst Associate). Experience with real-time data streaming technologies (e.g., Kafka, Azure Event Hubs). Familiarity with Data Governance and Data Quality frameworks. Exposure to MLOps concepts and tools. (ref:hirist.tech) Show more Show less