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Key Responsibilities:Design and develop ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT. Build and maintain data integration workflows from various data sources to Snowflake. Write efficient and optimized SQL queries for data extraction and transformation. Work with stakeholders to understand business requirementsespecially within insurance processes such as policy, claims, underwriting, billing, and customer dataand translate them into technical solutions. Monitor, troubleshoot, and optimize data pipelines for performance and reliability. Maintain and enforce data quality, governance, and documentation standards. Collaborate with data analysts, architects, and DevOps teams in a cloud-native environment. Must-Have Skills:Strong experience with Azure Cloud Platform services. Proven expertise in Azure Data Factory (ADF) for orchestrating and automating data pipelines. Proficiency in SQL for data analysis and transformation. Hands-on experience with Snowflake and SnowSQL for data warehousing. Practical knowledge of DBT (Data Build Tool) for transforming data in the warehouse. Experience working in cloud-based data environments with large-scale datasets. Mandatory: Strong insurance domain knowledge, including understanding of policy administration, claims processing, underwriting workflows, actuarial data, and regulatory/compliance standards (e.g., IRDAI, HIPAA where applicable). Good-to-Have Skills:Experience with DataStage, Netezza, Azure Data Lake, Azure Synapse, or Azure Functions. Familiarity with Python or PySpark for custom data transformations. Understanding of CI/CD pipelines and DevOps for data workflows. Exposure to data governance, metadata management, or data catalog tools. Knowledge of business intelligence tools (e.g., Power BI, Tableau). Qualifications:Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or a related field. 6+ years of experience in data engineering roles using Azure and Snowflake. Strong problem-solving, communication, and collaboration skills. ResponsibilitiesKey Responsibilities:Design and develop ETL/ELT pipelines using Azure Data Factory, Snowflake, and DBT. Build and maintain data integration workflows from various data sources to Snowflake. Write efficient and optimized SQL queries for data extraction and transformation. Work with stakeholders to understand business requirementsespecially within insurance processes such as policy, claims, underwriting, billing, and customer dataand translate them into technical solutions. Monitor, troubleshoot, and optimize data pipelines for performance and reliability. Maintain and enforce data quality, governance, and documentation standards. Collaborate with data analysts, architects, and DevOps teams in a cloud-native environment. Must-Have Skills:Strong experience with Azure Cloud Platform services. Proven expertise in Azure Data Factory (ADF) for orchestrating and automating data pipelines. Proficiency in SQL for data analysis and transformation. Hands-on experience with Snowflake and SnowSQL for data warehousing. Practical knowledge of DBT (Data Build Tool) for transforming data in the warehouse. Experience working in cloud-based data environments with large-scale datasets. Mandatory: Strong insurance domain knowledge, including understanding of policy administration, claims processing, underwriting workflows, actuarial data, and regulatory/compliance standards (e.g., IRDAI, HIPAA where applicable). Good-to-Have Skills:Experience with DataStage, Netezza, Azure Data Lake, Azure Synapse, or Azure Functions. Familiarity with Python or PySpark for custom data transformations. Understanding of CI/CD pipelines and DevOps for data workflows. Exposure to data governance, metadata management, or data catalog tools. Knowledge of business intelligence tools (e.g., Power BI, Tableau). Qualifications:Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or a related field. 6+ years of experience in data engineering roles using Azure and Snowflake. Strong problem-solving, communication, and collaboration skills. QualificationsQualifications:Bachelors or Masters degree in Computer Science, Data Engineering, Information Systems, or a related field. 6+ years of experience in data engineering roles using Azure and Snowflake. Strong problem-solving, communication, and collaboration skills. .
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.