Top Data & Analytics Jobs

Analyze complex data to solve business problems, build self-service data solutions, develop dashboards and metrics, and deliver strategic insights. Responsibilities also include data quality management, metadata and lineage governance, access controls, and collaboration with technology teams. The role requires scripting, data querying, business intelligence visualization, AWS development, and experience with structured and unstructured data.

Analyze business challenges and opportunities across product, marketing, and credit risk functions. Develop models, test hypotheses, make strategic recommendations, support pricing and customer experience strategies, and monitor implementation outcomes. Partner with IT, Sales, Operations, and Finance to improve profitability and performance. The role requires strong quantitative analysis, communication, business judgment, and execution skills.

Lead analytical strategy for Talent Development and Organizational Insights, translating talent and organizational data into actionable recommendations for product teams and executives. Responsibilities include framing business questions, developing metrics and models, influencing product roadmaps, creating reusable data products, managing concurrent analytical delivery, and partnering with product, engineering, design, People Science, HR, and senior leaders.

Designs, builds, and operates scalable cloud data platforms, APIs, pipelines, and data products. Leads architectural decisions, evaluates platforms such as Snowflake and Databricks, develops distributed and streaming workloads, enforces engineering standards, and mentors data engineers. Collaborates with product managers, software engineers, analysts, and data scientists to deliver resilient solutions. Requires extensive experience with application development, distributed data, SQL, programming, data pipelines, data modeling, cloud platforms, and relational and NoSQL databases.

Designs, builds, and operates scalable cloud data pipelines, platforms, and applications. Responsibilities include data modeling, distributed data processing, relational and NoSQL database development, architecture decisions, observability, streaming pipelines, and data warehousing. The role leads large-scale data initiatives, evaluates technologies such as Snowflake and Databricks, collaborates with product and engineering teams, communicates technical concepts, and mentors data engineers.

Leads data analysis and data product initiatives involving large databases, modeling, testing, reporting, process improvements, and product analytics. Manages and mentors junior analysts, partners with technology and business teams, supports data-system design, and develops strategic tests for products and marketing materials. Requires strong analytical, programming, business intelligence, communication, and leadership skills.

Design, build, test, and support scalable cloud data solutions and pipelines. Develop data platforms using Python, Spark, SQL, Databricks, Snowflake, relational and NoSQL databases, and cloud technologies. Establish reusable data engineering patterns, security controls, and operational standards. Collaborate with product managers, engineers, analysts, and data scientists; communicate technical outcomes; mentor data professionals; and deliver resilient, high-performance financial data products.

Analyzes complex data to support business strategies, develops self-service data solutions, dashboards, metrics, and visualization tools, and manages data quality, metadata, lineage, security, and access governance. The role requires scripting, querying, data management, Snowflake development, business intelligence, and collaboration with technology and business teams.

Design, build, and maintain data solutions for Retail Bank. Mine varied data sources, develop BI dashboards and metrics, drive analysis for business insights, and enforce data quality, lineage, and governance working with tech teams and Snowflake/AWS platforms.

Lead data analytics strategy, mine and analyze large-scale datasets, build and validate models, improve reporting and operational processes, evaluate products and marketing initiatives, and consult on data systems. Manage and mentor junior analysts, collaborate across business units, oversee concurrent projects, and apply business intelligence tools to support customer experience and organizational decision-making.