Senior BI Analyst (Tableau and Snowflake) at Blend360 · Hyderabad

companyDescription As a Senior BI Analyst(Tableau), you'll transform raw data into stunning visual narratives that spark action and drive decisions across multiple regions and cross-functional teams. Collaborate with global clients, craft jaw-dropping dashboards, and lead end-to-end BI projects that deliver real business value. If you're passionate about turning insights into impact, thrive in a fast-paced consulting-style environment, and are excited about the future of AI-powered analytics — we want you on our team! We're looking for someone with deep expertise in Tableau, SQL, Snowflake, and Python, and a strong knack for working across teams — including Data Engineers, Business Analysts, Regional Leads, and business stakeholders — to turn complex, multi-regional data into clarity. jobDescription End-to-End BI Implementation: Lead BI projects from requirement gathering to dashboard delivery, including data modelling, deployment, and user training — often spanning multiple regions and time zones. Tableau Development: Build dynamic, high-performance Tableau dashboards using advanced calculations, LOD expressions, parameter actions, set actions, drill-throughs, dashboard extensions, and custom visualizations to deliver compelling data stories. Snowflake & SQL Data Transformation: Write efficient SQL for data extraction, transformation, and analysis within Snowflake and across platforms like Databricks or Azure SQL. Leverage Snowflake's capabilities including Snowpark, virtual warehouses, and data sharing for optimized analytics. PySpark experience is an added advantage. Python Development & Automation: Leverage Python for data manipulation, transformation scripting, automation of repetitive workflows, and building lightweight data pipelines. Use libraries like pandas, NumPy, and scikit-learn to enhance analytics workflows and prototype AI/ML solutions that complement your BI delivery. Client & Cross-Functional Collaboration: Work closely with stakeholders across diverse regional teams to define KPIs, translate business needs into actionable insights, and deliver impactful analytics that resonate globally. Collaborate hands-on with Data Science (DS) and Data Engineering (DE) teams throughout the project lifecycle — partnering with DS teams to integrate model outputs and predictive insights into dashboards, and with DE teams to ensure robust data pipelines, validated source-to-report logic, and consistent data quality across layers. Cross-Tool BI Integration: Integrate Tableau with tools like Snowflake, Excel, and data pipeline platforms; assist in dashboard migration, Tableau Server/Cloud administration, and embedded analytics. Gen AI & Gen BI Initiatives: Actively contribute to Generative AI and Generative BI initiatives — leveraging Python to explore AI-driven analytics, natural language querying, automated insight generation, and intelligent dashboard experiences to push the boundaries of traditional BI. qualifications 4 to 6 Years of hands-on BI experience, with a strong focus on Tableau, SQL, Snowflake, and Python, delivering impactful analytics solutions across diverse business domains and multiple geographies. A strong understanding of data visualization best practices and BI architecture ensures that your dashboards and reports are both visually compelling and highly functional. Snowflake proficiency is a must — you bring solid experience in writing optimized queries, working with Snowflake's architecture (warehouses, stages, schemas), and leveraging its ecosystem for scalable analytics. Python proficiency is a must — you've used it in professional settings for data wrangling, automation, scripting, and analytical workflows. You're comfortable with libraries like pandas, NumPy, and have working familiarity with ML frameworks — not just classroom exposure, but real project experience. Excited to work on Gen AI and Gen BI innovations/automations using Python apart from the day-to-day project work — you're not just keeping up with AI, you're leaning into it and eager to implement AI-powered solutions that redefine how insights are delivered. Experience in implementing BI solutions for complex, multi-regional business scenarios — you solve real-world challenges through data-driven insights and thrive when working across cultural and functional boundaries. Proven ability to work alongside Data Science and Data Engineering teams — you understand how models, pipelines, and dashboards fit together and canbridge the gap between these functions to deliver cohesive, end-to-end analytics solutions. Standing out from the crowd with your unique expertise and problem-solving abilities, you contribute as a key team member in cross-functional, globally distributed teams. Known as a go-getter, you approach every project with enthusiasm and drive, ensuring high-quality and timely delivery, even in fast-paced, multi-stakeholder environments. As a mentor and collaborator, you pave the way for others, contributing to a positive, innovative team dynamic — regardless of region or role. Your innovative mindset helps you find creative ways to leverage data and AI, consistently turning insights into actionable strategies. Not just a hard worker but a fun one — you help foster an enjoyable work environment where collaboration and innovation thrive, making the journey as rewarding as the outcome. Ability to work in a fast-paced environment and handle multiple projects across regions simultaneously. additionalInformation Good to Have Snowflake Certification (e.g., SnowPro Core / Advanced) — demonstrates depth beyond day-to-day usage and strengthens your credibility with data platform stakeholders. Tableau Certification (e.g., Tableau Desktop Specialist / Certified Data Analyst) — always a plus when evaluating candidates and signals commitment to the craft. React JS experience — useful for building custom embedded analytics interfaces or interactive data applications. Not required, but it'll set you apart. Familiarity with other BI tools such as Power BI or Qlik Sense — broadens your perspective and helps in cross-tool migration or multi-platform environments. PySpark experience for large-scale data processing — an added advantage when working with big data workloads alongside Snowflake and Python.