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Vice President - Principal Data Engineer About this role Role Overview Data and AI are central to our platform and competitive advantage. We are seeking a Senior / Principal Data Engineer (12 years) to design, build, and operate largescale, enterprise data platforms, with deep AI/ML and GenAI expertisenot only enabling AI use cases, but using AI as a firstclass tool to design, build, and optimize data pipelines. This role is a handson senior engineering position with architectural ownership, operating at the intersection of data engineering, AI/ML systems, and platform modernization. Key Responsibilities Architect, build, deploy, and operate scalable ETL/ELT data pipelines supporting analytics, ML, and GenAI workloads. Use AI/ML and GenAI to design and build data pipelines, including: AIassisted pipeline and schema design; AIgenerated and optimized transformation logic and code; automated test generation, data validation, and performance tuning; AIdriven documentation and operational runbooks.Apply AI/ML techniques to automate data engineering workflows, including ingestion, schema evolution, data quality checks, anomaly detection, and pipeline optimization.Build and maintain feature engineering pipelines, training datasets, and feedback loops for production ML and GenAI systems.Enable GenAI use cases, including unstructured data ingestion, retrieval pipelines (RAG), and governanceaware AI data flows.Ensure enterprise standards for reliability, observability, lineage, security, and compliance across all data and AI pipelines.Partner with product, program, analytics, and AI teams in Agile delivery models to translate business needs into scalable AIenabled data solutions.Provide senior technical leadership through architecture reviews, mentoring, and setting data & AI engineering standards. Required Qualifications 12 years of experience owning and operating largescale data engineering platforms in production. Strong handson expertise in Python and SQL, with deep experience on cloud data platforms (AWS, Azure, or GCP).Proven experience architecting distributed, highperformance data systems.Demonstrated experience using AI/ML or GenAI to design, build, or optimize data pipelines (not just consuming AI outputs).Strong experience supporting ML/AI systems in production, including feature pipelines, data validation, monitoring, and retraining support.Solid understanding of data modeling, performance tuning, DevOps/CICD, and Agile delivery.Excellent communication skills and ability to operate in fastpaced, crossfunctional environments. Preferred / Plus Skills Experience with GenAI/LLM ecosystems (e.g., RAG, vector data, prompt or model lifecycle support).Experience with microservices, APIs, and largescale analytics platforms.Prior experience leading or mentoring senior engineers (playercoach model).Experience working in financial services or regulated environments. Why This Role This role goes beyond traditional data engineering. You will use AI to fundamentally change how data pipelines are designed, built, and operated, while delivering missioncritical data and AI platforms at enterprise scale. Our benefits To help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about. Our hybrid work model BlackRocks hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock. Guidance on AI use for candidates At BlackRock, AI has long been part of how we work enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, weve provided guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self. .
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.