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We are looking for an accomplished Lead Data Engineer to drive the architectural design, development, and optimization of our enterprise-scale data ecosystem. In this senior role, you will spearhead the build-out of highperformance data pipelines, enforce rigorous data quality and validation frameworks, and ensure endtoend reliability, scalability, and integrity of data flows across the organization. You will play a pivotal role in shaping our data engineering strategy, enabling advanced analytics and missioncritical, datadriven decision-making within our insurance-focused business domains. Responsibilities Lead the design and implementation of scalable data architectures on Azure, leveraging Databricks, Delta Lake, and related Azure data services. Build and optimize highvolume ETL/ELT pipelines using PySpark, SQL, Databricks Workflows, and Delta Live Tables. Define and enforce best practices for data engineering across notebooks, jobs, CI/CD, Unity Catalog, security, and workspace governance. Integrate and orchestrate data pipelines using Azure Data Factory, Azure Synapse pipelines, or Azure Databricks Workflows. Drive performance tuning for Spark jobs, cluster configurations, and data storage layers to balance speed and cost efficiency. Implement robust data quality and validation frameworks using tools like Great Expectations, DLT expectations, or custom PySpark checks. Ensure compliance, governance, and lineage tracking through Unity Catalog, Purview integration, and RBAC/ABAC policies. Architect endtoend data solutions supporting analytics, ML, actuarial models, and business-critical reporting workloads. Evaluate new Databricks features, MLflow enhancements, Photon execution, serverless compute, and recommend adoption strategies. Familiar with working on Agile methodologies - scrum, sprint planning, backlog refinement etc.Qualifications 8-12 years experience on Data Engineering role working with Databricks & Azure Cloud technologies. Bachelors degree in computer science, Information Technology, or related field. Strong proficiency in PySpark, Python, SQL. Strong experience in data modeling, ETL/ELT pipeline development, and automation Hands-on experience with performance tuning of data pipelines and workflows Proficient in working on Azure cloud components Azure Data Factory, Azure DataBricks, Azure Data Lake etc. Experience with data modeling, ETL processes, Delta Lake and data warehousing. Experience on Delta Live Tables, Autoloader & Unity Catalog. Preferred - Knowledge of the insurance industry and its data requirements. Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy. Excellent communication and problem-solving skills to work effectively with diverse teams Excellent problem-solving skills and ability to work under tight deadlines. .
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.