Top Senior Data & Analytics Jobs

Leads enterprise API governance operations, including API inventory reconciliation, data-quality analysis, KPI/KRI reporting, governance controls, audit support, remediation tracking, and process improvement. Partners with engineering, architecture, security, risk, and technology leadership teams to resolve findings, maintain governance documentation, and present inventory health, compliance, and operational risk insights. Requires advanced analytical, communication, regulatory compliance, and subject-matter expertise.

Lead hands-on development and operation of production data pipelines and platforms using PySpark, Python, SQL, and AWS services. Translate requirements into technical designs, data models, SLAs, and reliable pipeline architectures. Establish engineering, data quality, observability, documentation, and coding standards; conduct code reviews; mentor engineers; manage Agile delivery and releases; and use GenAI tools to improve productivity and solution quality.

Leads the strategy, architecture, development, and optimization of Neighborly’s AWS data platform, data lake, and enterprise data pipelines. Partners with marketing, analytics, data science, and business teams to deliver trusted data for customer engagement, reporting, AI/ML, and GenAI. Establishes engineering standards, governance, monitoring, quality, and operational processes while leading and developing a high-performing data engineering team.

Design, build, and optimize scalable AWS and Snowflake data pipelines, databases, data models, and cloud-based solutions. Implement ETL/ELT workflows, data quality and monitoring frameworks, CI/CD pipelines, automated recovery, documentation, and performance improvements. Collaborate with stakeholders and cross-functional teams in an Agile environment while conducting advanced analysis using Python and SQL.

Develops market intelligence and analytical solutions using data mining, modeling, forecasting, scenario planning, and visualization. Partners with marketing, sales, supply chain, strategy, finance, and commercial stakeholders to manage data logistics, build data tools, validate outputs, identify market opportunities, and communicate actionable recommendations. Manages multiple projects, presents insights to executive audiences, and supports strategic decision-making.

Owns TrendAI’s AI-generated answer visibility measurement program, including baselines, prompt methodology, recurring reporting, citation and competitive analysis, and entity representation. Translates findings into actionable content, PR, social, and messaging recommendations, partners with cross-functional teams to implement them, and evaluates outcomes. Requires enterprise B2B technology experience, AI visibility expertise, marketing analytics, knowledge-graph familiarity, technical fluency, and people-leadership readiness.

Designs and maintains BI solutions, writes optimized SQL and stored procedures, and builds AI-assisted reports and dashboards using Power BI, Tableau, and Excel. Translates business questions into actionable insights for Sales and cross-functional teams, develops data models, supports reporting migrations, and ensures data quality, governance, documentation, and consistency across platforms.

Lead development of compliance dashboards, automated reports, and integrations between trade compliance systems and ERPs. Translate regulatory data into visuals, manage integration and implementation projects, coordinate cross-functional teams, and serve as subject-matter expert to drive compliance improvements and automation.

Designs and maintains Power BI reports, dashboards, semantic models, and end-to-end analytics solutions. Builds ETL processes, data pipelines, and data transformations, performs advanced SQL/DAX/M work, automates reporting (including approved AI tools), validates data quality, recommends process improvements, and presents insights to technical and non-technical stakeholders. Individual contributor who may lead moderate-risk projects and deliver user training.

Build and maintain scalable data platforms and systems that transform raw market data into validated analytical datasets, including bars, residuals, curves, volatility surfaces, and greeks. Collaborate with trading, research, and external vendor teams to understand datasets and workflows, implement calculations, document technical solutions, and ensure reliable delivery through strong testing and validation practices.