At IBM - Confluent, we’re creating a category that transforms how every company manages and streams data.
Have you ever found a new favorite series on Netflix, picked up groceries curbside at Walmart, or paid for something using Square? That’s Confluent in action—giving our customers instant access to massive amounts of real-time data, enabling them to thrive in an ever-changing digital world.
As one of the fastest-growing enterprise companies in history, and with Fortune 100 customers across major industries, we have a tremendous opportunity in front of us. We also have experience on our side. Our leaders have taken companies of our size to major success before and include some of the original creators of Apache Kafka®.
We’re looking for self-motivated team members who crave a challenge and feel energized to roll up their sleeves and help realize Confluent’s unlimited potential. Chart your own path and take healthy risks with the backing and support of our #OneTeam culture. Be part of inclusive initiatives like Employee Resource Groups and development programs, and take advantage of benefits that support our diverse global teams. Grow as we grow—whether you’re just starting out or managing a large team, you’ll be amazed at the magnitude of your impact.
The mission of the Data team at Confluent is to serve as the central nervous system of all things data for the company. We build trusted data foundations, analytics products, semantic layers, dashboards, and decision-support systems that help teams move faster with confidence. Our BI organization is evolving beyond traditional reporting toward a modern Analytics Engineering model focused on reusable data models, governed self-serve data, an
Your role and responsibilitiesWe’re looking for a BI Developer / Analytics Engineer to accelerate analytics for Finance, Field Operations and adjacent GTM stakeholders including Sales, Customer Success, and partner-facing teams.
This role is ideal for someone who combines strong business intuition with modern analytics engineering craft. You will partner closely with business stakeholders, Data Scientists, and Data Engineers to translate business questions into trusted datasets, production-grade transformations, semantic definitions, and high-quality dashboards or self-serve analytics experiences.
Successful candidates will bring strong SQL and data modeling skills, a product mindset for analytics, and the ability to balance speed with reliability, governance, and scale.
What You'll Do
Partner with stakeholders across Field Operations, Sales, Customer Success, and related teams to understand business processes, define metrics, and translate requirements into scalable analytics solutions.
- Build and maintain trusted datasets, reusable data models, and semantic definitions using SQL-first analytics engineering practices on top of the warehouse.
- Develop and maintain production-grade ELT workflows and transformations using tools such as BigQuery, dbt, Airflow, and Git-based development practices.
- Provide analytical insights for MBRs/QBRs through deep dives, proactively identify data and process gaps and fixing them
- Deliver high-quality dashboards and self-serve analytics experiences using BI and analytics tools such as Tableau, Hex, and emerging semantic-layer or modern BI platforms where relevant.
- Improve data quality, governance, and observability by driving documentation, testing, lineage, access controls, and root-cause analysis in partnership with Data Engineering and platform owners.
- 5+ years of experience in BI, analytics, or analytics engineering roles, with strong hands-on dexterity of data modeling, SQL development, analysis and dashboard/reports delivery.
- Strong sense of ownership , proactive communication to understand and drive cross timezone partnership with both upstream and downstream stakeholders
- Expert SQL skills and solid experience working with modern cloud data warehouses such as BigQuery, Snowflake, or Databricks; experience with dbt and orchestration tools such as Airflow, Dagster, or Prefect is strongly preferred.
- Proven experience building scalable semantic models, trusted datasets, or curated reporting layers that improve self-serve analytics and metric consistency.
- Experience with BI and analytics tools such as Tableau, Hex, Looker, Power BI, or similar, with the ability to choose the right serving layer for the business use case.
Strong stakeholder management, communication, and problem-solving skills, with the ability to work cross-functionally and convert ambiguous business needs into well-governed analytical solutions
Preferred technical and professional experience- Experience in B2B SaaS, especially in GTM, customer, product usage, or financial analytics domains.
- Python coding skills to create optimized re-usable data functions, API integrated solutions
- Experience working with CRM and business systems data such as Salesforce, finance systems, product telemetry, or customer/account data models
- .Experience of driving /executing critical BI or Cloud services migration and best practices involved
- Curiosity and awareness about AI-assisted analytics workflows, conversational analytics, and the future of governed self-serve data experiences.
- Familiarity with analytics governance practices such as RBAC, sensitive data controls, metric standardization, semantic layer design, and trusted dataset certification.
Experience with data quality and observability tooling, performance optimization, or cost-aware warehouse design
Years of Experience:5 - 8
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