🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
Job Description Senior Data Engineer / Consultant About GyanSys: GyanSys is a global systems integrator and technology consulting company that helps enterprises accelerate digital transformation through SAP, Cloud, Data & Analytics, AI, and Intelligent Automation solutions. We partner with leading technology providers to deliver innovative, scalable, and business-driven solutions across diverse industries worldwide. Senior Data Engineer / Consultant Location: Bengaluru | Pune | Hyderabad Employment Type: Full-Time Experience: 4+ Years Joining: Immediate Joiners Preferred Job Summary GyanSys is looking for experienced Senior Data Engineers / Consultants to join our growing Data & Analytics practice. The ideal candidate will have strong hands-on experience in designing, developing, and optimizing enterprise-scale data engineering solutions across modern cloud and data platforms. The role requires expertise across technologies such as Microsoft Fabric, Azure Data Engineering, Databricks, PySpark, Apache Spark, Python, SQL, and cloud data platforms . The candidate will work closely with architects, business stakeholders, data scientists, and cross-functional teams to build scalable data pipelines and analytics solutions. Key Responsibilities Design, develop, and maintain scalable ETL/ELT data pipelines for enterprise data platforms. Develop data engineering solutions using Microsoft Fabric, Azure Data Factory, Databricks, PySpark, Spark SQL, and Python . Build data pipelines for structured, semi-structured, and unstructured data . Work with Microsoft Fabric components such as Fabric Data Factory, Lakehouse, Warehouse, Dataflows, and Notebooks. Develop and optimize Databricks notebooks, Spark jobs, Delta Lake pipelines, and Databricks Workflows . Implement Medallion Architecture and modern Lakehouse/Data Platform architectures. Integrate data from multiple sources including SQL Server, Oracle, PostgreSQL, APIs, cloud storage, ERP systems, and SaaS applications . Design and implement efficient data models, data warehouses, data lakes, and Lakehouse solutions . Optimize data pipelines, Spark jobs, SQL queries, clusters, and storage for performance and cost efficiency . Implement data quality, validation, monitoring, governance, security, and compliance practices. Develop and maintain CI/CD pipelines using Azure DevOps/GitHub and Git . Troubleshoot production issues and provide root-cause analysis and performance improvements. Collaborate with solution architects, business analysts, data scientists, and BI teams. Participate in technical design, code reviews, documentation, and knowledge-sharing initiatives. Mentor junior engineers and contribute to technical best practices within the team. Required Technical Skills Primary Skills 4+ years of experience in Data Engineering Strong hands-on experience with Microsoft Fabric and/or Azure Data Engineering Strong experience with Databricks, PySpark, Apache Spark, Spark SQL, and Python Strong SQL skills and experience with relational databases Hands-on experience developing ETL/ELT pipelines Experience with Azure Data Factory / Fabric Data Factory Strong understanding of Data Lake, Lakehouse, Data Warehouse, and Data Modeling Experience with Delta Lake Experience with Medallion Architecture Experience with cloud platforms, preferably Microsoft Azure Experience with Git, Azure DevOps/GitHub, and CI/CD Experience working with databases such as SQL Server, Oracle, PostgreSQL, Snowflake , or similar platforms Secondary Skills Power BI report/dashboard development and data integration Tableau or other BI/visualization platforms Databricks Unity Catalog Databricks Workflows Microsoft Fabric governance and security Kafka, Azure Event Hubs, or other streaming technologies Azure Synapse Analytics Microsoft Purview APIs and real-time data integration Exposure to Microsoft Fabric Dataflows Gen2 / Direct Lake Agile/Scrum methodologies Preferred Experience Experience designing end-to-end enterprise data platforms Experience migrating traditional ETL/data warehouse workloads to Azure, Databricks, or Microsoft Fabric Experience with real-time/streaming data pipelines Experience implementing data governance, security, lineage, and access controls Experience working with enterprise ERP systems such as SAP Experience with performance tuning and cost optimization of cloud data platforms Experience working with global clients and distributed teams Qualifications Bachelor's or Master's degree in Computer Science, Information Technology, Engineering , or a related field. 4+ years of professional experience in Data Engineering or related roles. Preferred Certifications Microsoft Certified: Fabric Data Engineer Associate Microsoft Certified: Azure Data Engineer Associate Databricks Certified Data Engineer Associate/Professional AWS Certified Data Engineer / Data Analytics Google .
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.