The Azure Data Engineer will build data pipelines and dataflows, implement security modules, and work with Azure services while supporting business requirements and data analysis.
This is a remote position.
Roles & Responsibilities:
- Understand business requirement and actively provide inputs from Data perspective.
- Understand the underlying data and flow of data.
- Build simple to complex pipelines & dataflows.
- Work with other Azure stack modules like Azure Data Lakes, SQL DW, etc.
- Should be able to implement modules that has security and authorization frameworks.
- Recognize and adapt to the changes in processes as the project evolves in size and function.
Requirements
Knowledge, Skills & Abilities:
- Expert level knowledge on Azure Data Factory.
- Expert level knowledge of SQL DB & Data warehouse (e.g. Microsoft SQL Server 2012/2016 & SSIS)
- Should know at least one programming language (e.g. C#, Visual Basic .NET, C++ .NET, PowerShell)
- Should be able to analyse and understand complex data.
- Knowledge of Azure data lake is an added advantage.
- Knowledge of other Azure Services like Analysis Service, SQL Databases will be an added advantage
- Excellent interpersonal/communication skills (both oral/written) with the ability to communicate at various levels with clarity & precision
Similar Jobs
Cloud • Information Technology • Business Intelligence • Consulting
Design, build, and deliver production-ready Data & AI solutions on Microsoft Azure. Develop and maintain data pipelines and lakehouse architectures using Fabric, Databricks, and Azure services; implement CI/CD, optimize production workloads, and collaborate with architects, project teams, and clients.
Top Skills:
AzureAzure Data FactoryAzure Data Lake StorageAzure DevopsAzure SqlAzure StorageCopilot StudioDatabricksGitMicrosoft CopilotMicrosoft FabricPysparkPythonSQLT-Sql
Information Technology • Professional Services • Software • Consulting
Design, build and maintain secure, high-quality data pipelines on Azure (Data Factory, Databricks, Synapse). Cleanse, transform and optimise large event-based datasets, implement data quality/observability, develop ETL scripts, stored procedures, and CI/CD pipelines, and participate in testing and troubleshooting.
Top Skills:
SparkAzureAzure Data FactoryAzure DatabricksAzure SynapseCi/CdETLPysparkPythonSparkSQL Server
Software
Design, build, and maintain batch and real-time ETL/ELT data pipelines and workflows. Automate ingestion, aggregation and logging; ensure data accuracy, security, and compliance. Implement data warehouse and lake solutions, mentor junior engineers, and collaborate with stakeholders to meet business requirements.
Top Skills:
AdfAdls Gen2AirflowAthenaAWSAws QuicksightAzureAzure Sql DbAzure SynapseBigQueryCassandraData LakesData WarehousesEc2EmrFivetranGCPGlueGlue EtlHadoopHiveIamJavaLambdaMapreduceMatillionMongoDBNeo4JNumpyPandasPower BIPythonRdsRedisRedshiftS3ScalaSnowflakeSparkSQLStitchTableau
What you need to know about the Delhi Tech Scene
Delhi, India's capital city, is a place where tradition and progress co-exist. While Old Delhi is known for its rich history and bustling markets, New Delhi is defined by its modern architecture. It's clear the region places a strong emphasis on preserving its cultural heritage while embracing technological advancements, particularly in artificial intelligence, which plays a central role in shaping the city's tech landscape, fueled by investments in research and development.
