Lead Data Engineer - Microsoft Azure , Synapse Data Engineering (Fabric)
Australia 13 days ago
Job Description
Location: Gurugram,Haryana,India
About US:-
We turn customer challenges into growth opportunities.
Material is a global strategy partner to the world’s most recognizable brands and innovative companies. Our people around the globe thrive by helping organizations design and deliver rewarding customer experiences.
We use deep human insights, design innovation and data to create experiences powered by modern technology. Our approaches speed engagement and growth for the companies we work with and transform relationships between businesses and the people they serve.
Srijan, a Material company, is a renowned global digital engineering firm with a reputation for solving complex technology problems using their deep technology expertise and leveraging strategic partnerships with top-tier technology partners. Be a part of an Awesome Tribe
Job Title:Lead Data Engineer (Microsoft Azure , Synapse Data Engineering (Fabric))
Job Responsibilities:
Design and Develop Data Pipelines:Hands on with development, and optimisation of scalable and reusable - data pipelines inAzure Microsoft Fabric Synapse Data Engineering, leveraging bothbatchandreal-time processing techniques. Ensure smooth integration withAzure Data Factoryfor orchestration and workflow management.
Cloud Data Architecture:Collaborate with theData Architecture teamto design and implement robust data architectures in theAzure environment, ensuring they align with business needs while optimising performance, scalability, and cost-efficiency.
Pipeline Optimisation :Continuously monitor and optimise the performance, cost, and reliability of data pipelines, ensuring efficient processing, storage, and management of large datasets.
Cross-functional Collaboration:Work closely withdata engineering teams,analysts, andbusiness stakeholdersto understand data requirements, developing solutions that enable self-service analytics and support the decision-making process.
Documentation& Knowledge Sharing:Contribute to internal documentation, fostering a culture of knowledge-sharing. Providementorshipand guidance to junior engineers, helping to elevate team skills and improve overall team performance.
Microsoft Fabric Experience:Apply your knowledge ofAzure Tech Stackon Data Engineering (or your willingness to learn)Fabric-based developmentto manage end-to-end data orchestration, governance, and security across cloud and on-premises systems, ensuring seamless data movement and integration across hybrid environments.
Data Modelling Expertise:Leverage your deep expertise inAzureto design and implementdata models, create processing pipelines, and integrate with otherAzure serviceslikeData LakeandSynapseto support data storage and analytics needs.
Required Skills and Qualifications:
Experience with Azure Ecosystem (Preferably Synapse):5+ years of hands-on experience withAzure Ecosystem, includingSynapse,Spark,OneLake, and other Fabric tools. Expertise in optimisingFabric notebooksand efficiently managing large-scale data workloads.
Proficiency in Azure Data Factory:Strong experience with designing and orchestrating complex data pipelines usingAzure Data Factory, with an emphasis on seamless data flow integration across various Azure services.
Familiarity with Microsoft Fabric:A working knowledge or eagerness to learnAzure Data Fabric, focusing on cross-platform data orchestration, governance, and security.
Advanced Data Engineering Skills:Extensive experience in data engineering, including the design and implementation ofETL processesand working with large datasets. Proven expertise indata quality, monitoring, and testing practices.
Cloud Architecture Design Expertise:Experience designing and implementingdata architecturesin theAzure ecosystem, including tools such asData Lake,Synapse, andAzure Storage.
SQL and Data Modelling Expertise:Strong skills inSQLanddata modelling, with the ability to design optimised data structures, tables, and views. Knowledge of both transactional and analytical data modelling.
Collaboration and Communication Skills:Strong ability to work cross-functionally with teams from various domains. Ability to communicate complex technical concepts to both technical and non-technical stakeholders.
Cost Optimisation:Proven experience optimisingdata engineering processesandAzure resourcesfor both performance and cost, particularly in large-scale cloud environments.
Preferred Skills:
Data Lakehouse Experience:Familiarity withData Lakehousearchitectures, particularly with tools likeDelta Lake,OneLake, etc.
Azure Ecosystem Familiarity:Knowledge ofAzure’s full ecosystemfor end-to-end data integration and ETL processes.
Proficiency in PySpark and Python:Expertise inPySparkfor data processing tasks, with a solid foundation inPython.
Fabric Integration:Familiarity withFabricand how it integrates with other services within theAzure ecosystem.
Databricks Experience:Experience withDatabricksis a plus.
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