Strategic Project Lead / Delivery Manager 

Data Annotation & AI Delivery

8+ Years of Experience

Position Overview

We are looking for a seasoned Delivery Manager (8+ years of experience) to lead large-scale data annotation and curation projects in support of cutting-edge LLM and multimodal AI research. You will oversee end-to-end delivery for projects with 100+ team members, ensure world-class data quality, and drive process and tooling innovation in collaboration with AI researchers and cross-functional teams.

This role is ideal for someone who combines deep technical expertise, proven leadership in managing large teams, and a passion for advancing AI/ML innovation. Given that our key customers operate in the data analytics, data engineering, and Business Intelligence (BI) space, the ideal candidate will bring hands-on leadership experience with platforms such as Databricks and Snowflake, enabling them to deeply understand customer domains, speak their language, and deliver annotation outcomes that are contextually relevant and technically sound.

Primary Responsibilities

1. Team Leadership & Development

• Lead, mentor, and grow large-scale teams of annotators and trainers.
• Drive performance management, career development, and targeted training.
• Foster a culture of excellence, ownership, and continuous learning.
• Design and implement motivation strategies (including gamification) to boost engagement and reward top performers.

1. Project Management & Coordination

• Define and manage project scope, objectives, timelines, and quality metrics.
• Align with cross-functional stakeholders on goals and deliverables.
• Proactively identify and resolve delivery risks, blockers, and dependencies.
• Provide clear and consistent reporting on progress, challenges, and solutions.

1. Data Quality & Integrity

• Own quality control and data integrity across the annotation lifecycle.
• Analyze datasets to identify trends, anomalies, and insights for improvement.
• Implement best practices for annotation, evaluation, and data curation.
• Share learnings and continuously improve quality processes.

1. Technical Collaboration & Innovation

• Partner with engineering and research teams to optimize internal tooling.
• Stay ahead of emerging trends in AI, ML, and multimodal processing.
• Champion innovations that reduce task completion times and improve efficiency.
• Maintain clear and scalable documentation for processes and training.

1. Customer & Domain Engagement

• Serve as a domain-knowledgeable point of contact for customers operating in data engineering, analytics, and BI environments.
• Leverage hands-on experience with platforms like Databricks and Snowflake to understand customer data workflows, terminology, and quality expectations.
• Translate customer-specific data engineering and BI contexts into clear, actionable annotation guidelines and quality benchmarks for delivery teams.
• Collaborate with customers to define annotation taxonomies and evaluation criteria that align with their data pipeline and analytics use cases.

Required Skills & Qualifications

• 10+ years of experience in engineering, program management, or delivery of large-scale projects.
• Proven ability to lead and scale large teams (100+ members) with measurable impact.
• Strong technical grounding in AI/ML, data annotation, and multimodal systems.
• Hands-on leadership experience in data analytics, data engineering, or BI domains, with working knowledge of platforms such as Databricks and/or Snowflake (architecture, pipelines, data modeling, and production workflows).
• Familiarity with the modern data stack including ETL/ELT pipelines, data warehouses, data lakes, and BI tools (Power BI, Tableau, Looker, or similar).
• Ability to translate complex data engineering and analytics concepts into annotation frameworks, quality standards, and training materials.
• Proficiency in Python (preferred) or Swift for data analysis and automation.
• Strong mathematical and analytical skills for data-driven problem solving.
• Experience in data curation, annotation pipelines, and quality control.
• Excellent communication and stakeholder management skills.
• Track record of driving high-quality outputs under tight deadlines.

Preferred Skills & Qualifications

• Advanced degree in Computer Science, Data Science, AI, or related fields.
• Experience applying gamification to workforce engagement.
• Familiarity with modern project management tools & methodologies.
• Exposure to state-of-the-art multimodal AI technologies.
• Prior experience managing annotation or data labeling projects for customers in the data engineering, analytics, or BI space.
• Familiarity with SQL at an advanced level and data orchestration tools such as Apache Airflow, dbt, or Prefect.
• Certifications in Databricks (e.g., Data Engineer Associate) or Snowflake (e.g., SnowPro Core) are a plus.

Who We Are:

Galaxy is a global leader in digital assets and data center infrastructure, delivering solutions that accelerate progress in finance and artificial intelligence. We believe that blockchain and digital asset innovation will transform how value moves through the world – and we’re building the products and services to make that future a reality.
 
Our institutional digital assets platform spans trading, investment banking, asset management, staking, self-custody, and tokenization technology. We also invest in and operate cutting-edge data center infrastructure to power AI and high-performance computing, addressing the growing demand for scalable energy and compute in the U.S.
 
We work at the intersection of finance and technology, helping institutions, startups, and developers navigate a digitally native economy. Led by CEO and Founder Michael Novogratz, our team blends deep crypto expertise with institutional experience and a shared commitment to shaping the future of Web3 and AI.
 
Galaxy is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia.
 
To learn more about our businesses and products, visit www.galaxy.com.

What We Value:

We are a diverse team of free thinkers, and fast movers united to help investors and creators energize the global economy. We are looking for individuals who thrive in a culture of builders and overachievers and embrace high performance, transparent feedback, and a mission-first approach. Our culture shapes our way of working and gets us where we want to be.

• Seek Excellence.
• Be Selective To Be Effective.
• Be Highly Aligned, Loosely Coupled.
• Disagree Transparently.
• Encourage Independent Decision-Making.
• Build Dream Teams.

Who You Are:

Galaxy is hiring a Data Engineering Manager to lead and grow our Data Engineering team. This role is ideal for an experienced data engineering professional who has a strong technical foundation and a track record of delivering scalable data platforms in fast-paced environments.
As a Data Engineering Manager, you will balance hands-on technical leadership with team management, driving execution on key data initiatives while mentoring engineers and improving development practices.

What You’ll Do:

• Partner across Galaxy’s business lines (Trading, Custody, Asset Management, Mining) to build and enhance a reliable and scalable data platform
• Drive execution of the data engineering roadmap in alignment with business priorities
• Lead and mentor a team of data engineers, supporting their growth and ensuring high-quality delivery
• Design, build, and maintain scalable data pipelines (batch and streaming)
• Develop and operate high-throughput, low-latency data processing systems
• Work within the Databricks and Spark ecosystem to support large-scale data workloads
• Build and maintain cloud-native data solutions on AWS
• Leverage dbt for transformation, data modeling, testing, and documentation
• Use Airflow (or similar orchestration tools) to manage and schedule data workflows
• Establish and enforce best practices around code quality, testing, CI/CD, monitoring, and reliability
• Collaborate closely with product, analytics, and infrastructure teams to deliver impactful data solutions
• Contribute to technical design decisions and continuously improve system performance and developer productivity

What We’re Looking For:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field
• 8+ years of experience in data engineering or distributed systems
• 4+ years of experience managing or mentoring engineers
• Strong hands-on experience with AWS, Databricks/Spark, and modern data architectures
• Experience building and operating both batch and streaming data pipelines
• Hands-on experience with dbt for transformations and Airflow (or similar) for orchestration
• Solid understanding of data modeling, data quality, and production data systems

What We Offer:

• Competitive base salary and discretionary bonus
• Competitive paid time off
• Great office location in central Mumbai (BKC) 
• Company-paid health and protective benefits for employees and their eligible dependents
• Free virtual coaching sessions through Headspace
• Opportunities to learn about the Crypto industry
• Smart, entrepreneurial, and fun colleagues

*Benefits may vary depending on location.

Join our dynamic and high-impact Data team as a Data Engineer, where you'll be responsible for safely receiving and storing trading-related data for the India teams, as well as operating and improving our shared data access and data processing systems. This is a critical role in the organisation as the data platform drives a huge range of trader analysis, simulation, reporting and insights. The ideal candidate should have work experience in systems engineering, preferably with prior exposure to financial markets and with proven working knowledge in the fields of Linux administration, orchestration and automation tools, systems hardware architecture as well as storage and data protection technologies.

Your Core Responsibilities:

• Manage and monitor all distributed systems, storage infrastructure, and data processing platforms, including HDFS, Kubernetes, Dremio, and in-house data pipelines
• Drive heavy focus on systems automation and CI/CD to enable rapid deployment of hardware and software solutions
• Collaborate closely with systems and network engineers, traders, and developers to support and troubleshoot their queries
• Stay up to date with the latest technology trends in the industry; propose, evaluate, and implement innovative solutions

Your Skills and Experience:

• 5–7 years of experience in managing large-scale multi-petabyte data infrastructure in a similar role
• Advanced knowledge of Linux system administration and internals, with proven ability to troubleshoot issues in Linux environments
• Deep expertise in at least one of the following technologies: Kafka, Spark, Cassandra/Scylla, or HDFS
• Strong working knowledge of Docker, Kubernetes, and Helm
• Experience with data access technologies such as Dremio and Presto
• Familiarity with workflow orchestration tools like Airflow and Prefect
• Exposure to cloud platforms such as AWS, GCP, or Azure
• Proficiency with CI/CD pipelines and version control systems like Git
• Understanding of best practices in data security and compliance
• Demonstrated ability to solve problems proactively and creatively with a results-oriented mindset
• Quick learner with excellent troubleshooting skills
• High degree of flexibility and adaptability