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Role Summary:
Were seeking a dynamic System Engineer to design and deliver intelligent scalable and reliable data systems. This hybrid role combines data engineering AI/ML integration system reliability and DevOps to accelerate data collection enable intelligent workflows and drive business impact. Youll collaborate across engineering data analytics and business teams to build reusable frameworks reduce time-to-value and uphold engineering excellence.
Key Responsibilities:
Data & AI Workflow Engineering
Accelerate data collection at scale from millions of sources using robust scalable pipelines.
Design build and deploy workflows that combine AI/ML models with human-in-the-loop systems.
Operate as a full-stack data engineer taking projects from problem formulation to production.
Develop APIs and services to expose data and model outputs for downstream consumption.
System Engineering Reliability & DevOps
Build and maintain CI/CD pipelines for data and ML services using Azure DevOps or GitHub Actions.
Implement observability (metrics logs traces) and reliability features (retries circuit breakers graceful degradation).
Optimize data workflows and infrastructure for performance scalability and fault tolerance.
Contribute to infrastructure-as-code (IaC) for provisioning and managing cloud-native environments.
Platform & Framework Development
Elevate development standards through reusable services frameworks templates and documentation.
Champion best practices in code quality security and automation across the engineering lifecycle.
Collaborate with engineering teams across the business to improve time-to-value and share internal solutions.
Collaboration & Business Impact
Collaborate with engineering teams across the business to improve time-to-value and share internal solutions.
Translate business problems into data science/ML solutions with measurable outcomes.
Propose pragmatic diverse approaches to solving business challenges using data and AI.
Present results and recommendations clearly to technical and non-technical audiences using compelling storytelling and visualizations.
Required Skills and Qualifications:
5-8 years of experience in data engineering machine learning or system/platform engineering.
Strong programming skills in Python/DotNet or Java; proficiency in SQL DBT and data orchestration tools (e.g. Airflow).
Experience with containerization (Docker) and Kubernetes on Azure and/or AWS.
Proficiency in CI/CD Git and cloud-native development.
Familiarity with observability tools (Azure Monitor Prometheus Grafana) and data validation frameworks (e.g. Great Expectations).
Familiarity with data science libraries (Pandas NumPy scikit-learn) and deploying ML models to production.
Strong understanding of distributed systems microservices and API design.
Bachelors or Masters degree in computer science Data Science Engineering or a related field.
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.
About BlackRock
At BlackRock we are all connected by one mission: to help more and more people experience financial well-being. Our clients and the people they serve are saving for retirement paying for their childrens educations buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.
This mission would not be possible without our smartest investment the one we make in our employees. Its why were dedicated to creating an environment where our colleagues feel welcomed valued and supported with networks benefits and development opportunities to help them thrive.
For additional information on BlackRock please visit @blackrock Twitter: @blackrock LinkedIn: is proud to be an Equal Opportunity Employer. We evaluate qualified applicants without regard to age disability family status gender identity race religion sex sexual orientation and other protected attributes at law.
Required Experience:
IC
Full-Time