Jobs at Dynata

Manages client relationships and supports account growth by qualifying RFPs, writing proposals, developing pricing, coordinating bids, supporting project delivery, and contributing to sales presentations. Partners with Account and Sales Directors to expand revenue, upsell services, manage expectations, and maintain CRM records. Requires at least one year of relevant sales or customer service experience, strong communication skills, Microsoft Office proficiency, and travel as needed.

Designs, builds, and maintains scalable batch and streaming data pipelines, lakehouse medallion architectures, transformation layers, and data models. Develops PySpark and SQL solutions, integrates diverse data sources, implements data quality monitoring, and manages infrastructure as code. Troubleshoots pipeline and data incidents, participates in code reviews, collaborates with architects, and mentors junior and mid-level engineers.

Leads enterprise semantic layer, data, and AI platform architecture. Defines lakehouse, medallion, data model, data contract, metadata, schema governance, feature store, model lifecycle, and interoperability standards. Partners with product, engineering, platform, and data science teams to create secure, reusable foundations for analytics, machine learning, and AI applications. Translates business and governance requirements into scalable technical architectures and provides thought leadership across enterprise data and AI enablement.

Leads Dynata’s Consumer Intelligence product portfolio, defining strategy, roadmap, business cases, pricing, packaging, commercialization, and growth objectives. Transforms proprietary panel, survey, profile, and behavioral data into scalable commercial products. Conducts customer and market discovery, drives product development and adoption, aligns cross-functional stakeholders, and builds a product management team as the portfolio expands.

Leads enterprise AI transformation by developing the AI roadmap, prioritizing investments, managing initiative portfolios, and delivering measurable business value. Partners with executives and cross-functional teams to redesign operations, establish governance, evaluate technologies and vendors, drive adoption, and lead workforce change. Accountabilities include revenue growth, productivity, efficiency, customer experience, compliance, AI maturity, and value realization.

Leads graph analytics, identity resolution, forecasting, and predictive modeling initiatives for operational, commercial, and product decisions. Designs scalable graph data models, production-ready machine learning solutions, and time-series forecasts. Establishes validation, monitoring, governance, and experimentation practices while partnering with product, engineering, and platform teams. Translates complex analytical findings into business recommendations and provides technical leadership across graph science, forecasting, optimization, and decision-support capabilities.

Build and maintain CI/CD pipelines, infrastructure automation, Kubernetes-based data platform environments, and observability tooling. Manage Terraform and Helm deployments, cloud cost optimization, provisioning, policy enforcement, incident response, capacity planning, and operational documentation. Collaborate with data engineering and security teams to improve reliability, scalability, compliance, and engineering productivity across enterprise lakehouse platforms.

Design and implement enterprise data quality frameworks for lakehouse platforms. Build automated validation tests, dashboards, anomaly detection, observability solutions, and CI/CD quality checks. Manage data quality SLAs, profile new sources, resolve incidents, collaborate with governance and source owners, and educate engineering and product teams on quality standards.

Leads information security, data privacy, and regulatory compliance for an enterprise data lakehouse platform. Defines access controls, encryption, classification, and security frameworks; manages risk assessments, threat modeling, vulnerability testing, audits, incident response, and remediation. Partners with engineering teams to embed controls into CI/CD and data workflows, maintains compliance evidence, and trains teams on secure data handling.

Partner with APAC business units and sales to produce monthly revenue and P&L reporting, lead budgeting and forecasting, build financial models and presentations, validate new systems (CRM/D365), identify cost savings and risks, support audits and controls, and provide strategic financial insight to senior stakeholders.

Perform data validation, delivery, and tabulation for low-complexity projects. Interpret client requirements, organize and shape data to internal standards, produce outputs, and escalate issues to managers as needed.