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What's the role? We are looking for a strong AI Data Engineer to help make HERE data AI-ready for the CoE's portfolio of use cases, building the pipelines, integrations, data products, and governed access patterns that enable AI solutions, agents, and automations to operate on trusted information. This role works across enterprise systems, platforms, and business domains to resolve data quality, fragmentation, metadata, and access challenges that often prevent AI initiatives from moving beyond pilot stages into scalable production deployments. As a critical member of the AI Center of Excellence, the AI Data Engineer transforms data readiness from a recurring executive concern into a measurable organizational capability, ensuring AI solutions are built on reliable, secure, and accessible data foundations. What You'll Do Build AI-Ready Data Foundations Design, build, and maintain scalable data pipelines that support AI, machine learning, generative AI, and agent-based solutions. Develop connectors and integrations across enterprise applications, databases, SaaS platforms, APIs, and knowledge repositories. Create reusable data services and data products that accelerate AI use case delivery across the company. Ensure AI systems can access high-quality, current, and trusted information through robust retrieval and integration patterns. Enable AI Solutions at Scale Partner with AI Solution Architects, Data Scientists, Product Owners, and Business Stakeholders to understand data requirements for AI use cases. Design and implement architectures supporting agentic workflows, Retrieval-Augmented Generation (RAG), semantic search, and AI-driven automation. Establish standardized patterns for structured and unstructured data ingestion, transformation, and access. Support the transition of AI solutions from pilot initiatives to enterprise-scale production deployments. Improve Data Quality and Governance Identify and resolve data quality, consistency, lineage, and ownership issues across business domains. Implement monitoring, validation, and observability mechanisms to ensure data reliability. Work with Security, Privacy, and Governance teams to ensure AI solutions comply with company policies and regulatory requirements. Define and maintain metadata, cataloging, and governance standards that improve discoverability and trust in enterprise data. Drive Enterprise Collaboration Partner with business, technology, and data teams to prioritize data readiness initiatives supporting the AI roadmap. Influence platform and application owners to adopt AI-friendly data practices. Help establish enterprise best practices for AI data architecture, governance, and operational support. Contribute to the broader AI CoE strategy by identifying systemic data challenges and recommending long-term solutions. Who are you? Required Qualifications Bachelor's/ Master's degree in Computer Science, Information Systems, Data Engineering, Software Engineering, or a related field. 5+ years of experience in data engineering, integration engineering, or data platform development. Experience designing and building enterprise-scale data pipelines using modern cloud and data platform technologies. Strong understanding of data modeling, ETL/ELT processes, APIs, event-driven architectures, and data integration patterns. Experience working with both structured and unstructured data sources. Proficiency with SQL and at least one modern programming language such as Python, Java, or Scala. Experience working with AWS cloud platform and kubernetes Strong problem-solving skills and the ability to work across complex organizational environments. Experience supporting AI, machine learning, generative AI, or agentic AI solutions. Familiarity with vector databases, embeddings, semantic search, and Retrieval-Augmented Generation (RAG) architectures. Experience with data governance, metadata management, data catalogs, and data lineage tools. Understanding of data privacy, security, and responsible AI principles. Experience with modern orchestration and integration tools such as Airflow, Databricks, Snowflake, Azure Data Factory, Kafka, or similar platforms. Experience building enterprise APIs and reusable data services. Knowledge of M365 Copilot, Copilot Studio, Azure AI Foundry, AWS Bedrock, or similar AI ecosystems. Success Characteristics Systems thinker who can connect business outcomes to underlying data capabilities. Pragmatic problem solver who balances speed of delivery with governance and quality. Passionate about unlocking the value of enterprise data through AI. Strong communicator capable of working with executives, business leaders, architects, and engineering teams. Comfortable operating in ambiguous environments and helping shape emerging AI capabilities. What We Offer Hybrid model of work Challenging problems to solve Collaborative and encouraging colleagues Opportunities to learn, grow and develop: company hackathons, technical talks, and trainings Regular feedbacks Paid vacation days A great work-life balance Flexible working hours Competitive salary plus bonus Medical coverage for you and your family (in Poland) This role is eligible for Creative Tax Incentive scheme in Poland” or KUP (Autorskie Koszty Uzyskania Przychodu) (in Poland) Option to work on a B2B contract (please note: benefits, bonus and KUP do not apply in this case- in Poland) Diverse team of fantastic & talented people from 60+ countries worldwide. Brown bag talks, team events, BBQ on the rooftop and more! Change is HERE. Apply Now! Our culture is founded on openness, collaboration and honesty, with colleagues who are brilliant in their field, helpful, resilient, loyal and strive for the best. One team in that everyone makes a difference and everyone is heard. As part of HERE Technologies employment process, candidates will be required to successfully complete a pre-employment screening process. This offer and any related claims are subject to the successful completion of a pre-employment screening. This will involve employment, education, and criminal verification if applicable. HERE is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, age, gender identity, sexual orientation, marital status, parental status, religion, sex, national origin, disability, veteran status, and other legally protected characteristics. Who are we? HERE Technologies is a location data and technology platform company. We empower our customers to achieve better outcomes – from helping a city manage its infrastructure or a business optimize its assets to guiding drivers to their destination safely. At HERE we take it upon ourselves to be the change we wish to see. We create solutions that fuel innovation, provide opportunity and foster inclusion to improve people’s lives. If you are inspired by an open world and driven to create positive change, join us. Learn more about us on our YouTube Channel.
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.