Top Data & Analytics Jobs

Design and implement customer data solutions using Adobe Experience Platform and RTCDP. Configure XDM schemas, datasets, identities, and real-time profiles. Build ingestion pipelines, audience segmentation, and activation strategies. Ensure data quality, governance, and optimize platform performance while collaborating with marketing and technical teams.

Leads an analytics engineering team developing governed, scalable data models, semantic layers, and BI frameworks. Owns dbt, Snowflake, and Looker practices; establishes modeling, testing, documentation, metric, and governance standards; and enables trusted self-service analytics. Partners with data and business teams to translate requirements into technical solutions, deliver strategic data assets, track OKRs, and communicate insights to executives. Provides mentorship, resource allocation, project oversight, and hands-on technical leadership.

Lead product-focused analytics for customer-facing interfaces: define and maintain interface metrics, measure design system adoption, run large-scale A/B tests, optimize localization, partner with Product/Design/Engineering, and enable data-driven decision making across teams.

Design, build, and operate scalable batch and streaming data pipelines, lakehouse and warehouse models, and data services. Own datasets end to end, improve Snowflake, Iceberg, Spark, and Flink performance and reliability, implement governance and observability, and support graph-serving data models. Partner with product and engineering teams, participate in on-call, review code and designs, and mentor junior engineers.

Build and scale data pipelines, APIs, integrations, and data models supporting CRM personalization, segmentation, audience activation, and campaign measurement. Ensure pipeline reliability through monitoring, alerting, and logging; automate workflows; document systems; participate in architecture and code reviews; and mentor junior engineers. Collaborate with data engineering, data science, and CRM teams to improve personalized email, push, and SMS engagement for millions of users.

Designs and maintains scalable data pipelines and platform architecture using Python, dbt, Airflow, and Snowflake. Responsibilities include data modeling, ELT development, quality and observability, production debugging, source-data validation, performance optimization, and Tableau reporting. The role leads ad hoc analysis, collaborates with engineering, marketing, product, and leadership teams, makes architectural decisions, and mentors colleagues through code reviews and knowledge sharing.

Develop scalable data pipelines and data systems supporting economic insights, analytics, and machine learning. Build and optimize solutions using Python, Spark, Hive, Impala, Hadoop, and Databricks while helping migrate on-premises infrastructure to the cloud. Design data architectures and schemas, improve system performance and reliability, write tested code, and collaborate with data scientists, product managers, and infrastructure teams throughout the development lifecycle.

Partner with commercial and delivery teams to build scalable reporting, KPIs, dashboards and forecasts. Analyse sales, pre-sales and delivery performance to reduce time-to-revenue, improve deal velocity, and provide data-driven recommendations to drive commercial growth.

Leads enterprise data engineering, analytics, governance, and AI initiatives for Corporate & Investment Banking Finance. Designs scalable data architectures, pipelines, curated datasets, semantic models, and cloud reporting platforms. Drives data quality, lineage, metadata management, reporting modernization, workflow automation, generative AI adoption, and responsible AI practices. Partners with senior Finance, Technology, and Data Management stakeholders to deliver enterprise data products and transformation programs.

Leads a client-facing healthcare analytics team that designs and maintains prior authorization decision automation programs. Consults PaaS clients, develops strategic roadmaps, translates requirements into technical blueprints, analyzes authorization and claims data, and builds KPI reports using visualization tools. Manages direct reports, improves analytics processes and AI tooling, partners with product and engineering teams, and ensures automation outcomes and client KPIs are achieved.