Real Estate & Construction
Full-Time
Tech Mahindra
Overview
Job Summary
- 8+ years of IT experience and must have worked in DW project for at least 3 years
- Worked in atleast 3 Data Warehousing projects by contributing in developing ETL solution.
- Proficient with Python+ Pyspark for data manipulation+ analysis+ and extraction
- Advance SQL : Should be very strong understanding of Database & Data Modelling. Must posses hands-on experience in writing complex SQLs
- Azure Data Factory (ADF): A key service for data integration and orchestration. Should know how to create data pipelines+ schedule activities+ and manage data movement and transformation using ADF
- Azure Databricks: A cloud-based big data analytics platform based on Apache Spark. Should be adept at using Databricks for data engineering tasks like data ingestion+ transformation+ and analysis
- Azure SQL Database: Microsoft's fully managed relational database service. Should be proficient in using it for data storage+ retrieval+ and basic manipulation.
- Azure DevOps: Knowledge of Azure DevOps is valuable for implementing Continuous Integration and Continuous Deployment (CI/CD) pipelines for data engineering solutions
- Monitoring and Optimization: Understanding how to monitor the performance of data engineering solutions and optimize them for better efficiency is crucial
- Data Quality and Data Cleaning: Knowing how to ensure data quality and perform data cleaning operations to maintain reliable data is important for data engineers.
- Data Modeling and ETL/ELT: You should be skilled in data modeling techniques and Extract+ Transform+ Load (ETL) or Extract+ Load+ Transform (ELT) processes for data integration.
- Good to have Apache Spark: Understanding of Spark and its various components. Spark is a fast and general-purpose data processing engine that can run in-memory+ making it well-suited for iterative algorithms and interactive data analysis.
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