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Data Engineer

Alkegen · Pune - IN
// classified as
Other (Adjacent or hard to classify.)
posted
1d ago
location
Pune - IN
languages
go, python, sql
tools
azure, snowflake, spark
> stack
gopythonsqlazuresnowflakesparknumpypandas
> description

Job Requirements

Why work for us?  
 
Alkegen brings together two of the world’s leading specialty materials companies to create one new, innovation-driven leader focused on battery technologies, filtration media, and specialty insulation and sealing materials. Through global reach and breakthrough inventions, we are delivering products that enable the world to breathe easier, live greener, and go further than ever before.   
 
With over 60 manufacturing facilities with a global workforce of over 9,000 of the industry’s most experienced talent, including insulation and filtration experts, Alkegen is uniquely positioned to help customers impact the environment in meaningful ways.  
 
Alkegen offers a range of dynamic career opportunities with a global reach. From production operators to engineers, technicians to specialists, sales to leadership, we are always looking for top talent ready to bring their best.  Come grow with us!

Job Responsibilities:  

We are seeking a skilled Data Engineer to design, build, and maintain integrated and reporting-focused data marts, ensuring reliable, well-modelled datasets that support enterprise reporting, cross-domain analytics, and self-service BI use cases. The role will play a pivotal role in our data warehouse modernization initiative, transforming legacy SQL-based data transformations into scalable Spark-based solutions on Microsoft Fabric. 

 

Key Responsibilities: 

  • Architect and manage the integration layer, ingesting data from multiple ERP databases, ensuring standardized, reconciled, and scalable data models that enable downstream reporting and analytics. 

 

  • Develop and maintain reporting layer datasets that are well-modelled, performant, and optimized for Power BI consumption. 

 

  • Support day-to-day operational data engineering activities, including designing, developing, and maintaining SQL stored procedures and data transformations to deliver reporting-layer datasets that meet ongoing business and BI requirements. 

 

 

  • Analyze, refactor, and enhance existing SQL procedures and pipelines to improve performance, scalability, reliability, and business logic coverage. 

 

  • Collaborate closely with business stakeholders, ERP teams, and cross functional technical teams to understand data requirements, align on integration approaches, and deliver reliable, analytics ready data solutions. 

 

  • Monitor and troubleshoot ETL pipelines, SQL stored procedures, and data transformation jobs to ensure reliable and timely data delivery. 

 

  • Ensure data quality, consistency, and governance across modernized and operational data assets. 

 

  • Implement best practices for data modelling, transformation logic, and documentation within the Microsoft Fabric ecosystem. 

 

Required Skills & Qualifications: 

Education: Bachelor’s degree in Computer Science, Information Technology, Engineering or related field 

 

Experience: 3–5 years of experience architecting and maintaining scalable ETL/ELT pipelines, with a deep technical focus on Azure Data Factory and the Microsoft Fabric ecosystem. 

 

 

Technical Skills 

  • Data Warehousing: Strong expertise in Medallion Architecture (Bronze–Silver–Gold) design and data flow, Strong grasp of dimensional modelling concepts (star schema, snowflake schema, facts, and dimensions). Experience designing data marts and semantic layers for reporting purposes.  

 

  • Advanced SQL: Advanced proficiency in SQL Server, including T-SQL, stored procedures, and query optimization. Strong understanding of relational database concepts, query optimization, indexing, and execution plans. Experience with T-SQL, PL/SQL, or similar procedural SQL dialects. Hands on experience in analyzing and translating complex SQL procedures into Spark SQL and PySpark equivalents 

 

  • Microsoft Azure: Proven capability in developing modern ETL architectures using Azure Data Factory and Fabric Data Factory, integrating data from multiple enterprise sources into medallion-based lake house architectures. Proficient in monitoring and managing Data Factory pipelines, ensuring reliable execution, timely completion, and rapid issue resolution. 

 

  • Microsoft Fabric Ecosystem: Deep understanding of Fabric One Lake architecture, and data layering strategy (Bronze, Silver, Gold). Proficiency with Fabric pipelines, Fabric notebooks, integration with other Fabric services, and Fabric workspace management. Advanced understanding of Spark architecture, distributed processing concepts, partitioning strategies, and performance optimization techniques.  

 

  • Spark SQL: Proficient in Spark SQL for writing efficient distributed queries, optimizing execution plans, and leveraging Spark's SQL engine for complex data transformations. Strong ability to convert and optimize existing SQL procedures to Spark SQL equivalents while maintaining performance and accuracy. 

 

  • Python Programming: Strong Python skills with experience in Pandas, NumPy, and other data manipulation libraries. Clean coding practices, software engineering fundamentals, and ability to write maintainable, well-documented code. 

 

  • Power BI & Analytics: Practical knowledge of Power BI data models, dimensional relationships, and performance optimization (aggregations, query folding). Understanding how data mart design impacts BI tool performance and user experience. Experience collaborating with BI developers and analysts.  

 

  • Version Control : Proficiency in Git and version control best practices. Experience with CI/CD pipelines for notebook deployment. Familiarity with collaborative development workflows in Fabric environments. 

 

  • Agile & DevOps: Proficiency with Scrum methodologies and agile sprint planning. Strong hands-on experience with Azure DevOps for CI/CD pipelines, managing notebooks and artifacts, release management, and source code management. Experience managing work items, backlogs, and sprint artifacts within Azure DevOps. 

 

  • Stakeholder Collaboration: Excellent communication skills with ability to translate complex technical concepts for non-technical business stakeholders. Experience gathering and refining requirements from business teams and ERP developers. Proven ability to work effectively in cross-functional teams and manage expectations through iterative delivery cycles. 

 

  • AI Adoption: Hands‑on familiarity with AI‑enabled data engineering tools such as Microsoft Fabric Copilot and Azure OpenAI to assist in ETL/ELT development, code optimization, lineage creation, and pipeline monitoring & troubleshooting. 

 

Functional Skills 

  • Strong stakeholder management and communication skills. 

  • Strong analytical mindset to understand complex existing implementations and drive optimizations. 

 

  • Strong focus on security best practices across data pipelines and platforms. 

  • Ability to collaborate with cross-functional technical teams (commercial, operations, finance, supply chain) and drive results. 

  • Experienced in Agile development practices and sprint‑based delivery. 

  • Adept at utilizing generative AI tools (e.g., Azure Copilot, ChatGPT) as well as AI‑enabled data engineering tools to assist in development, optimization, monitoring, troubleshooting and governance in Microsoft Fabric and Azure environments. 

 

Good to Have 

  • Exposure to manufacturing or industrial domain analytics. 

  • Knowledge of Databricks or big data ecosystems. 

  • Familiarity with data governance and compliance frameworks. 

Apply at Alkegen →