Top Data & Analytics Jobs

Design and operate end-to-end infrastructure for intracortical neural data, from ingestion and validation through preprocessing, versioned dataset releases, and training data loaders. Preserve scientific metadata and provenance while implementing signal processing, quality checks, storage optimization, parallel processing, and monitoring. Collaborate with neuroscience, machine learning, infrastructure, and IT teams to support scalable, reliable model training and sensitive research-data management.

Leads enterprise data engineering, analytics, architecture, and AI solution delivery. Oversees teams, EDW and data lake architecture, Informatica pipelines, BigQuery data models, Tableau reporting, governance, security, quality, operational reliability, roadmaps, budgets, and stakeholder partnerships. Requires strong technical leadership, business translation, and hands-on expertise across data integration, warehousing, analytics, and governed AI solutions.

Leads complex enterprise data analysis, reporting, reconciliation, and validation initiatives across business, risk, compliance, and regulatory functions. Develops and optimizes advanced SQL solutions across databases, warehouses, cloud platforms, and legacy systems. Translates business requirements into scalable analytical solutions, investigates data anomalies, supports modernization and automation, and establishes data quality standards. Provides technical guidance and mentorship to analysts while collaborating with stakeholders and enterprise data teams.

Lead end-to-end data engineering workstreams, building reliable cloud pipelines, governed AI and retrieval workflows, trusted data models, event-driven systems, and automated recovery. Own production reliability, security, observability, cost optimization, testing, audit evidence, and operational readiness. Use Python, advanced SQL, coding agents, machine learning, and defensive AI engineering to deliver secure, resilient platforms while mentoring engineers and translating business needs into practical solutions.

Designs, builds, deploys, and operates scalable data pipelines, datalake systems, streaming and batch processing frameworks, MLOps infrastructure, data documentation tooling, and an agentic data exploration platform. The role improves engineering velocity, data reliability, observability, discoverability, and machine learning development across customer-facing products.

Develop and maintain scalable ETL/ELT pipelines and distributed data processing solutions using Python, PySpark, and AWS. Build cloud data solutions with S3, EMR, and Lambda; automate infrastructure with Terraform; integrate REST APIs, Kafka, and MQ; support Cassandra storage; orchestrate workflows with Airflow and Control-M; and troubleshoot performance, reliability, and data quality issues.

Designs and builds Babel Street’s petabyte-scale data platform, including ingestion, processing, storage, search, cloud migration, AI retrieval, governance, observability, and cost optimization. The role leads modernization from AWS to GCP, establishes scalable data pipelines and architecture standards, supports hybrid vector and graph retrieval, and provides technical leadership through design reviews, coding, mentoring, and incident escalation. It is a hands-on principal engineering position rather than a people-management role.

Develop slot-style electronic gaming math models using probability, C#, and a prize-first math engine. Translate game concepts into software, maintain mathematical metrics and PAR sheets, and support data-driven design decisions. Research North American slot market trends to ensure contemporary game designs. Collaborate with game designers and cross-functional teams while managing changing priorities. The role requires a mathematics-focused bachelor’s degree or equivalent experience, C# and Excel experience, and may involve overtime, weekend work, and limited travel.

Supports strategic and operational projects through research, data and financial analysis, presentations, project coordination, and process improvement. Assists with M&A due diligence and partner integration activities, including organizing information, tracking deliverables, and preparing status updates. The intern collaborates across functions, communicates findings, and develops practical experience in corporate finance, strategy, business analytics, and operations during a 10-week summer program.

Leads the Business Analytics and Reporting team, delivering business intelligence, dashboards, regulatory reporting, financial analyses, and executive insights. Partners with FP&A, strategic planning, and business stakeholders to explain performance drivers, risks, and recommended actions. Owns capital, retained earnings, and dividend calculations; modernizes reporting processes; improves controls and efficiency; and manages hiring, coaching, prioritization, and team development.