Top Data & Analytics Jobs

Lead and develop business strategies, manage teams, execute product and marketing strategies, and enhance credit risk performance through analytics and partnerships.

Lead Data Engineer responsible for designing, building, testing, and supporting scalable data pipelines and cloud-based solutions. Collaborate across Agile teams to optimize data models, ensure data quality and governance, mentor engineers, and apply distributed computing, streaming, and emerging GenAI tooling to deliver personalized marketing and messaging experiences.

Lead Data Engineer responsible for designing, building, and supporting scalable cloud data pipelines and platforms. Collaborate across Agile teams to implement distributed computing, data modeling, quality, governance, and real-time streaming solutions using Python, SQL, Snowflake/Databricks, Spark, Kafka, and cloud services. Mentor engineers, participate in code reviews, and drive technical innovation including GenAI tooling.

Lead analytics initiatives for credit card products by building data solutions, performing advanced analysis, creating BI dashboards, ensuring data quality and governance, and partnering with tech and business teams to enable self-service and drive strategic insights.

Lead enterprise analytical tool validation by designing frameworks, executing validation projects, assessing model quality and risk, prototyping best practices, communicating results, and mentoring junior staff. Partner cross-functionally to influence strategy and ensure analytical rigor across large data and open-source tool environments.

Lead Data Engineer responsible for building technical solutions, collaborating with Agile teams, utilizing big data technologies, and developing cloud-based data warehousing solutions to enhance user experiences.

As a Principal Data Analyst, you will innovate and manage data solutions, provide business intelligence, and ensure data quality for the Retail Bank.

Design and build data solutions using open-source technologies; enable self-service data consumption; partner with business to develop dashboards and insights; perform analysis; ensure data quality, metadata, lineage, and governance; collaborate with tech teams on security and data access; build monitoring and reporting for data quality.