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Overview We are seeking a Data Engineer to join our growing Data & Analytics team. This role is responsible for designing, developing, and maintaining data pipelines and enterprise data solutions while contributing to the continued evolution of our data architecture and analytics platform. The ideal candidate has a solid foundation in data engineering and enjoys working across multiple technologies to build scalable, reliable data solutions. This individual will partner closely with business stakeholders to understand requirements, develop data integration solutions, and support reporting and analytics initiatives. As our data platform continues to evolve, this role will have the opportunity to contribute to architectural decisions and gain experience with emerging technologies including Microsoft Fabric, Databricks, Snowflake, and AI-enabled development tools. This is a full-time, in-office position. Responsibilities Design, develop, and maintain ETL/ELT pipelines using Azure Data Factory, SQL Server, SSIS, and Python. Develop SQL queries, stored procedures, views, and database objects to support enterprise reporting and analytics. Build and maintain reliable data integrations from internal and external data sources. Partner with business users to gather requirements and translate business needs into technical solutions. Support the design and enhancement of enterprise data models and data architecture. Collaborate with BI developers to provide optimized datasets for Power BI reporting and semantic models. Utilize Azure DevOps and Git for source control, deployments, and CI/CD processes. Monitor, troubleshoot, and optimize data pipelines for performance and reliability. Contribute to data quality, governance, documentation, and engineering standards. Explore and leverage AI-assisted development tools to improve engineering productivity and solution quality. Continuously learn and evaluate emerging data platform technologies. Qualifications Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent experience). 3+ years of professional experience in data engineering or a related technical role. Strong experience with SQL, Microsoft SQL Server and T-SQL development. Experience developing ETL/ELT pipelines using Azure Data Factory or similar integration tools. Experience programming with Python. Experience working within Azure cloud environments. Experience using Git and Azure DevOps or similar source control and CI/CD platforms. Working knowledge of Power BI datasets and data modeling concepts. Experience gathering business requirements and working directly with stakeholders.Strong analytical, communication, and problem-solving skills. Experience or familiarity with AI-assisted development tools such as Microsoft Copilot, GitHub Copilot, ChatGPT, Codex, or similar technologies. Preferred Qualifications Experience with Microsoft Fabric, Databricks, or Snowflake. Knowledge of enterprise data architecture and data modeling principles. Experience with Azure Data Lake Storage. Familiarity with dimensional modeling and data warehouse concepts. Experience integrating REST APIs and semi-structured data. Interest in AI, advanced analytics, and modern cloud data platforms. Why Kimley-Horn? At Kimley-Horn, we do things differently. People, clients, and employees are at the forefront of who we are. Clients know we prioritize achieving their goals and growing their success. Employees know our culture and approach to business are built on a desire to provide an environment for everyone to flourish. Our commitment to quality is only as good as the people behind it— that’s why we welcome and develop passionate, hardworking, and proactive employees. We take pride in how our employee retention, robust benefits package, and company values have led to Kimley-Horn’s placement on the Fortune “100 Best Companies to Work” list for 19 years! Key Benefits at Kimley-Horn Exceptional Retirement Plan: 2-to1- company match on up to 4% of eligible compensation (salary + bonus) and additional profit-sharing contribution. Comprehensive Health Coverage: Low-cost medical, dental, and vision insurance options. Time Off: Personal leave, flexible scheduling, floating holidays, and half-day Fridays. Financial Wellness: Student loan matching in our 401(k), and performance-based bonuses. Professional Development: Tuition reimbursement and extensive internal training programs. Family-Friendly Benefits: New Parent Leave, family building benefits, and childcare resources.
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.