Top Data & Analytics Jobs

Leads Major League Soccer’s Marketing Science function, overseeing teams and external resources while developing marketing analytics strategy. Partners with Marketing, CRM, Technology, Product, and Data Engineering teams to improve audience targeting, personalization, campaign measurement, media investment, and fan growth. Oversees predictive modeling, AI and machine learning applications, media mix modeling, experimentation, attribution, and CRM activation. Communicates analytical insights and strategic recommendations to executive stakeholders across League and Club organizations.

Leads a small team responsible for SQL Server data warehousing, ETL pipelines, outbound data feeds, and enterprise Power BI. Oversees platform operations, governance, reliability, and self-service BI adoption while helping establish a Databricks and Azure cloud data platform. The role drives data modeling, quality, security, Agile delivery, vendor management, and stakeholder partnerships, while applying AI tools to improve engineering and analytics workflows.

Leads a data engineering team responsible for designing, developing, testing, deploying, and maintaining scalable data products and platforms. Sets technical direction, manages team performance and development, establishes engineering standards, and oversees data quality, security, governance, and operational excellence. Partners with product owners, enterprise architecture, information security, data governance, and business stakeholders to deliver data solutions. Defines team strategy and roadmap, evaluates emerging technologies, and communicates metrics and progress to senior leadership.

Analyze complex financial and organizational data using SQL, dbt, and Tableau to create dashboards, models, pipelines, and actionable recommendations. Collaborate with business partners to define analytics needs, validate results, document data assets, maintain reporting tools, provide technical assistance, and present insights to leadership. The role also includes peer review, project coordination, vendor evaluation, and mentoring junior analysts.

Build scalable data processing applications, ETL/ELT pipelines, AWS-based data solutions, and analytics integrations. The role involves optimizing high-throughput systems, supporting engineering analysis and optimization, working with structured and unstructured data, and collaborating across engineering teams. Candidates need a bachelor’s degree in engineering, U.S. citizenship, at least two years of software engineering experience, and proficiency in C# and Python.

Performs land-cover data production, quality assurance, remote-sensing and GIS analysis, and processing of raster and vector datasets. Responsibilities include working with imagery, LiDAR, elevation data, map services, metadata, automated GIS workflows, and derivative products such as maps, statistics, StoryMaps, and web applications. Supports NOAA coastal management projects independently and collaboratively.

Customer-facing technical leader who architects, builds, and optimizes large-scale data engineering and lakehouse solutions on Databricks. Supports pre-sales and delivery with POCs, performance/load testing, workload sizing, migrations, observability, and adoption through workshops and community engagement.

Leads enterprise data architecture and big data initiatives supporting mission and operational objectives. Designs scalable architectures for structured, semi-structured, and unstructured data; translates requirements into data systems, analytics, and visualization solutions; guides engineering teams; and develops strategies for high-volume, high-velocity, and real-time data environments. Collaborates with multidisciplinary teams to generate operational insights from complex datasets.

Enterprise Analytics interns support data analysis and visualization projects across healthcare operations. They conduct exploratory and advanced analytics, use Tableau and analytical tools, participate in the full project lifecycle, collaborate with analytics team members and business leaders, define business problems, and communicate actionable insights. The role offers flexible scheduling of up to 40 hours weekly.

Own the Finance and Operations data layer, integrating systems into Snowflake and Omni, building reusable data models, dashboards, governed metrics, validation checks, and reconciliation workflows. Partner with Finance, Operations, and Data teams to translate business processes into trusted analytics, improve data quality, automate reporting, and support leadership decision-making.