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Senior Data Engineer (Cloud Data Platforms & Big Data) - Manufacturing Domain Location: Pune, Maharashtra (Travel to Phaltan as required) Experience: 10+ Years Employment Type: Full-Time About the Opportunity We are looking for an experienced Senior Data Engineer to build, optimize, and maintain scalable enterprise data platforms that power advanced analytics, artificial intelligence, and business intelligence solutions. The ideal candidate should have extensive experience in cloud-based data engineering, modern data architectures, ETL/ELT development, and big data technologies while ensuring data quality, governance, security, and operational excellence. Key Responsibilities Data Pipeline Engineering Design, develop, test, deploy, and maintain scalable enterprise data pipelines. Build reliable batch, streaming, and near real-time data processing solutions. Develop reusable ETL/ELT frameworks for enterprise data integration. Optimize pipeline performance, scalability, reliability, and operational efficiency. Automate manual data workflows and improve overall data delivery processes. Data Platform & Architecture Design and maintain enterprise Data Lakes, Lakehouse, and Data Warehouse solutions. Develop reusable data models and curated datasets for analytics and AI. Partner with Data Architects and Solution Architects to implement enterprise data strategies. Follow modern software engineering practices including version control, testing, and deployment automation. Data Quality, Governance & Security Implement data validation, reconciliation, monitoring, and quality controls. Maintain metadata, lineage, transformation documentation, and data dictionaries. Ensure compliance with enterprise governance, security, and privacy standards. Monitor data platforms to ensure reliability, availability, and high performance. Collaboration Work closely with Data Scientists, Product Teams, Business Analysts, and Business Stakeholders. Translate business requirements into scalable technical solutions. Support AI and Analytics teams by delivering trusted, high-quality data products. Continuous Improvement Identify opportunities to improve existing data engineering standards and frameworks. Troubleshoot production issues and perform root cause analysis. Evaluate emerging cloud technologies and modern data engineering tools. Contribute to engineering best practices and knowledge sharing. Required Qualifications Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Engineering, or a related technical discipline. 10+ years of experience in Data Engineering, Big Data, or Cloud Data Platforms. Proven experience building enterprise-scale data solutions. Required Technical Skills Python SQL PySpark Scala Spark Java (Preferred) Databricks Azure Data Factory Azure Synapse Azure Data Lake Storage Snowflake ETL / ELT Development Data Warehousing Data Lakes & Lakehouse Architecture Batch & Streaming Data Pipelines Data Modeling (Star Schema, Snowflake Schema, Data Vault) CI/CD Practices Data Governance & Metadata Management Preferred Experience Experience supporting enterprise initiatives in: Pricing Analytics Manufacturing Analytics Predictive Maintenance Commercial Operations AI & Machine Learning Platforms Enterprise Cloud Data Solutions What We're Looking For Strong expertise in modern data engineering technologies. Excellent analytical and troubleshooting skills. Strong documentation and communication abilities. Ability to collaborate across cross-functional teams. Passion for building scalable, reliable, and governed data platforms. Interested candidates can share their updated resume at: anjali@brilcs.com .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.