Group Company: JSW Steel Limited
Designation: Business Intelligence Analyst
Role: (Senior Data Engineer)
Level: Manager/Senior Manager
Location: Mumbai - Seawoods location
Job Brief: As a Business Intelligence Analyst at JSW Steel Limited within the Sales IT & Digital Transformation department in the Manufacturing steel industry, you will play a crucial role in leveraging data to drive strategic decision-making processes. You will be responsible for analyzing complex data sets, creating visualizations, and providing actionable insights to enhance sales performance and optimize digital transformation initiatives.
We are seeking a highly skilled and experienced Senior Data Engineer to join our dynamic team. The ideal candidate will have a strong background in data engineering, with extensive experience in data visualization using Power BI, advanced Python programming, and cloud infrastructure on Azure. Additionally, expertise in using Databricks for large-scale data processing is essential.
This role offers the opportunity to work with cutting-edge technologies and collaborate closely with cross-functional teams to drive business growth and innovation.
Responsibilities:
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Data Architecture & Design: Lead the design and implementation of scalable data architectures that support complex analytics and business intelligence solutions.
- Data Integration & ETL: Develop, optimize, and maintain ETL pipelines using Python, Databricks, and Azure Data Factory to process and integrate data from various sources.
- Data Modelling: Design and implement robust data models that ensure data integrity and support efficient querying in Power BI and other analytical tools.
- Power BI Visualization: Create interactive and insightful dashboards and reports in Power BI, leveraging advanced DAX functions and Python scripts for enhanced visualizations.
- Azure Cloud Management: Manage and optimize data storage solutions using Azure services such as Azure Data Lake, Azure SQL Database, and Azure Synapse Analytics.
- Databricks Expertise: Utilize Databricks for large-scale data processing, including developing notebooks, managing clusters, and integrating with Azure-based data lakes.
- Performance Optimization: Monitor and optimize data processing and querying performance, ensuring the scalability and reliability of data pipelines.
- Collaboration: Work closely with data scientists, analysts, and business stakeholders to understand requirements, develop solutions, and deliver actionable insights.
- Documentation & Best Practices: Ensure comprehensive documentation of data pipelines, architecture, and processes. Advocate for and implement best practices in data engineering and cloud management.
Skills:
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Data analysis
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Business intelligence tools
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Data visualization
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Dashboard creation
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Stakeholder collaboration
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Process improvement
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SQL
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Data modeling
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ETL processes
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Problem-solving
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Attention to detail
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Industry knowledge
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Communication skills
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Critical thinking
Technical Skills:
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Power BI: Expert in building advanced dashboards, reports, and custom visuals, including the use of DAX and Python.
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Python: Proficient in Python for data manipulation, ETL processes, and integration with BI tools.
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Azure Cloud: Extensive experience with Azure services, including Azure Data Lake, Azure SQL Database, Azure Data Factory, and Azure Synapse Analytics.
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Databricks: Deep understanding of Databricks, including notebook development, cluster management, and performance tuning.
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SQL: Advanced knowledge of SQL for querying and data transformation.
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Data Modelling: Strong experience in designing and implementing data models for both operational and analytical purposes.
Soft Skills:
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Leadership: Demonstrated ability to lead projects and mentor junior team members.
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Communication: Strong verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
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Problem-Solving: Excellent analytical and problem-solving abilities, with a focus on delivering high-quality solutions.
Preferred Qualifications:
- Certifications: Relevant Azure certifications (e.g., Azure Data Engineer, Azure Solutions Architect) are a plus.
- Experience with Other Tools: Familiarity with other BI tools (e.g., Tableau), and experience with big data technologies (e.g., Hadoop, Spark) is advantageous.
- Industry Experience: Prior experience in [specific industry, e.g., Manufacturing, retail] is preferred but not required.
Required work experience
- Years of experience: 5 to 8 years
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Experience: 5+ years of professional experience in data engineering, with a proven track record of working on large-scale data projects.
