Top Data & Analytics Jobs

Migrates customer data from legacy and competitor systems into SaaS products using SQL-based tools. Performs extraction, transformation, cleanup, validation, auditing, data mapping, and quality assurance. Develops repeatable scripts and workflows, collaborates with customers and cross-functional teams, supports testing and defect resolution, and documents migration processes. The role increasingly uses BigQuery, cloud platforms, automation, and intelligent tools while supporting global delivery across regions and time zones.

Develop and maintain interactive dashboards, reports, scorecards, data models, and visual analytics solutions for a U.S. Navy weapon system program. Connect and optimize diverse data sources, implement calculations and row-level security, manage refreshes and data quality, document data lineage, and translate complex datasets into actionable visual narratives for technical and executive stakeholders.

Early Career Analyst supporting Affirm’s Risk & Analytics organization through data analysis, portfolio monitoring, reporting, risk and growth strategy insights, and cross-functional collaboration. The role uses SQL and Python to build scalable reports, support machine learning and risk model deployment, assess lending regulations, and improve product launches and market expansion. Analysts will integrate AI tools into workflows while validating outputs and developing expertise in consumer lending and quantitative business decision-making.

Develop market intelligence, forecasting, statistical models, scenario analyses, and automated reporting for supply chain decisions. Integrate internal and external datasets using Python, R, SQL, and other tools; build dashboards; support data governance; and translate analytical findings into recommendations for procurement, planning, and executive stakeholders.

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.

The Data Analyst supports Product and Partner Management leadership by aligning priorities, facilitating cross-functional collaboration, sharing knowledge, and analyzing business information. The role requires querying databases, using Excel and potentially business intelligence tools, evaluating risks and opportunities, supporting requirements gathering, leading meetings, and making informed business decisions while managing multiple priorities.

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.

Analyze customer support experiences and define success metrics at Remitly. Partner with product, program, engineering, and analytics teams to deliver insights influencing product and process design. Communicate metrics and recommendations to stakeholders, manage strategic analytics initiatives, build dashboards, model complex scenarios, conduct experimentation, and drive measurable business outcomes.

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.

Supports cross-channel marketing attribution and influence modeling by documenting data sources, defining business rules, mapping and normalizing interaction data, testing reporting prototypes, and recommending implementation steps. The intern also assists with AWS marketing data organization, segmentation research, data hygiene, process documentation, and stakeholder communications. The role requires analytical thinking, thorough documentation, clear communication, and collaboration across marketing and technical teams.