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Role Purpose The Analytical Engineer is responsible for transforming complex, raw data into trusted, analytics-ready datasets that support business intelligence, advanced analytics, and enterprise decision-making. This role bridges data engineering and analytics by combining data modelling, data transformation, and governance expertise to deliver high-quality data products. Key Responsibilities Design and implement scalable data models using Data Vault and dimensional modelling methodologies. Develop and maintain ETL/ELT pipelines to ingest, cleanse, and transform data into trusted analytical datasets. Deliver analytics-ready data to support reporting, dashboards, AI, and advanced analytics initiatives. Ensure data quality, governance, lineage, and compliance with enterprise standards. Collaborate with business stakeholders, architects, data scientists, and delivery teams to translate business requirements into data solutions. Contribute to Agile delivery teams, solution design, and continuous improvement of data engineering practices. Minimum Requirements Qualifications Bachelor's Degree in Computer Science, Information Systems, Engineering, Data Science, or a related field. Relevant Azure, Databricks, Microsoft Fabric, or cloud certifications are advantageous. Experience 5+ years' experience in Data Engineering, Analytics Engineering, or Data Warehousing. Experience designing enterprise data models and building cloud-based analytics solutions. Experience working within Agile project environments. Consulting experience is advantageous. Technical Skills Essential SQL and Python Data Vault and Dimensional Modelling ETL/ELT development Azure Data Factory Azure Databricks Microsoft Fabric Azure Synapse Analytics Power BI Data Warehousing Data Governance and Quality Frameworks Advantageous Snowflake Apache Spark Microsoft Purview Azure DevOps DataOps and CI/CD Streaming technologies (Kafka/Event Hub) Key Competencies Analytical thinking and problem-solving Strong stakeholder engagement and communication Attention to detail and data quality Collaborative and client-focused mindset Delivery-focused within Agile environments Governance and compliance awareness Success Measures Delivery of trusted, analytics-ready datasets. Implementation of scalable and reusable data models. Adherence to enterprise data governance and quality standards. Successful support of reporting, analytics, and AI initiatives. Contribution to high-quality client delivery and data product development. Desired Skills: Systems Analysis Complex Problem Solving Programming/configuration Critical Thinking Time Management
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.