Major League Soccer · 1 day ago
Senior Director, Data & Analytics Engineering-Fan Genome
New York, NY
Full-time
Hybrid
Director/Executive
$200K/yr - $230K/yr
10+ years expMajor League Soccer (MLS) has built Fan Genome, an advanced 360° fan intelligence platform. They are seeking a hands-on technical leader to own the architecture and evolution of MLS’s next-generation data platform, ensuring scalability, performance, and reliability while delivering robust analytics engineering frameworks.
Media and EntertainmentSoccerSports
Responsibilities
Own the technical architecture and feature delivery of MLS’s next-generation cloud-native Lakehouse platform ensuring scalability, performance, and reliability
Optimize and enhance existing real-time data pipelines built on Apache Kafka, Amazon Kinesis, and Apache Flink to maintain low-latency ingestion and event-driven processing at scale
Manage and improve distributed compute workflows leveraging Apache Spark for large-scale batch processing, advanced feature engineering, and ML-adjacent workloads
Oversee and refine open table format implementations (Apache Hudi, Apache Iceberg) to ensure ACID compliance, schema evolution, and efficient incremental processing
Drive performance tuning and cost optimization for zero-copy analytics using modern distributed, MPP, column-oriented OLAP systems designed for real-time, high-concurrency analytical workloads (e.g., StarRocks) and query engines like Presto
Maintain and extend robust data APIs for both batch exports and point (per-fan) queries, integrated with Fan Genome’s feature store
Advance identity resolution capabilities to ensure accurate, unified fan profiles across multiple data sources
Establish enterprise-grade governance and security with frameworks such as AWS Lake Formation for cataloging, lineage, and fine-grained access control
Work with BI team to deliver BI self-service and analytics engineering frameworks, including:
Designing semantic models, data contracts, and governed data for consistency and trust in reporting
Building curated wide tables (OBTs) and optimized query layers for high-performance dashboards and ad-hoc analysis
Implementing data modeling best practices, version-controlled transformations, and automated testing to ensure reliability and scalability
Build, mentor, and scale a world-class data and analytics engineering team, fostering a culture of technical excellence and innovation
Qualification
Required
Bachelor's degree in Computer Science or a related field required
10+ years of progressive experience in data engineering or platform engineering, including 8+ years in leadership roles with a proven track record of delivering production-grade, large-scale data and analytics platforms
Hands-on expertise in designing, deploying, and optimizing cloud-native data solutions on platforms such as AWS, Azure, or GCP
Deep understanding of modern data architecture patterns, including Lakehouse design, data mesh principles, and data quality monitoring frameworks
Demonstrated ability to translate complex business requirements into scalable technical solutions, collaborating with data management, security, and privacy teams to ensure compliance and governance
Strong computer science fundamentals with proficiency in at least one advanced programming language (Python, Scala, or Java)
Proven experience with distributed processing frameworks (e.g., Apache Spark, Apache Flink) and real-time streaming architectures
Expertise in Lakehouse data platforms built on object storage and open table formats (e.g., Apache Hudi, Apache Iceberg) for ACID transactions, schema evolution, and incremental processing
Proficiency in Infrastructure-as-Code, orchestration, transformation frameworks, containers, and observability tools
Familiarity with data science and machine learning workflows, including feature engineering, model training pipelines, and integration with feature stores
Deep BI and analytics expertise, including designing and implementing analytics engineering frameworks for governed, reusable data models
Building semantic layers and curated wide tables (OBTs) to enable BI self-service at scale
Applying data modeling best practices, version-controlled transformations, and automated testing for analytics pipelines
Enabling advanced analytics and experimentation platforms for marketing, personalization, and revenue optimization
Experience integrating with BI tools such as Tableau, Power BI, Looker, and optimizing query performance for high-concurrency workloads
Data Architecture & Engineering
Cloud-native Lakehouse design on object storage with open table formats (Hudi, Iceberg)
Zero-copy analytics: External catalogs for distributed query engines and OLAP databases
Streaming & Real-Time Processing
Apache Kafka, Amazon Kinesis, Apache Flink for event-driven pipelines and CDC
Distributed Compute & Batch Processing
Apache Spark for large-scale ELT, feature engineering, and ML workflows
BI Enablement & Advanced Analytics
Analytics engineering: Build curated wide tables (OBTs) and semantic layers for BI tools (Tableau, Power BI, Looker)
Performance optimization for modern MPP OLAP systems to support high-concurrency, low-latency queries at scale
Apply data modeling best practices for self-service analytics and experimentation
Feature store integration for ML and personalization use cases
Governance & Security
AWS Lake Formation or Microsoft Purview for fine-grained access control, lineage, and compliance
Data contracts, observability, and cost governance
Programming & Tooling
Strong SQL, Python, and Scala
Infrastructure-as-Code (Terraform/CloudFormation), CI/CD, and container orchestration (Kubernetes)
High-level of commitment to a quality work product and organizational ethics, integrity and compliance
Ability to work effectively in a fast paced, team environment
Strong interpersonal skills and the ability to effectively communicate, both verbally and in writing
Demonstrated decision making and problem-solving skills
High attention to detail with the ability to multi-task and meet deadlines with minimal supervision
Proficiency in Word, Excel, PowerPoint and Outlook
Preferred
Master's degree in Computer Science or a related field
Experience building customer or fan 360 platforms, identity resolution systems, and feature stores
Performance tuning for modern MPP OLAP systems and distributed query engines (e.g., Presto, Trino)
Strong background in self-service analytics strategies, data governance for BI, and cost optimization for analytical workloads
Knowledge of the Spanish Language (business proficiency)
Knowledge of the sport of soccer
Ability to travel and to work non-traditional hours, including evenings, weekends, and holidays
Benefits
Comprehensive medical, dental, and vision coverage
$500 wellness reimbursement
Generous Holiday and PTO schedule to promote work-life balance
On-the-job training
Feedback
Ongoing educational opportunities
Company
Major League Soccer
Major League Soccer is a professional sports league that organizes men's soccer competitions in the United States and Canada.
201-500 employees
H1B Sponsorship
Major League Soccer has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (2)
2024 (1)
Funding
Current Stage
Growth StageTotal Funding
$25MKey Investors
National Black Bank Foundation
2022-03-10Debt Financing· $25M
2018-06-01Series Unknown
Leadership Team
Chris Schlosser
Senior Vice President, Emerging Ventures
A
Alicia LaPorta
Director of Match Day Operations & Administration
Recent News
Sports Business Journal
2025-12-20
Sports Business Journal
2025-12-06
Sports Business Journal
2025-12-06
Company data provided by crunchbase