Role Description We're looking for a Team Lead to guide a team of analysts delivering high-quality market research outputs for our clients. You'll balance people leadership with hands-on oversight of data quality, ensuring your team consistently meets business and client standards. This role suits someone who enjoys coaching others while staying close to the data — especially household panel data and survey-based research. - Lead, coach, and motivate a team of analysts to consistently deliver high-quality, client-ready work - Set clear performance goals and track progress through regular feedback - Mentor team members to strengthen their analytical and technical skills over time - Maintain open, transparent communication across the team to keep projects on track - Spot skill or knowledge gaps within the team and organize relevant training - Act as an escalation point for complex or ad hoc client requests Qualifications - Bachelor's degree (any field) with a genuine interest in survey or market research - 3+ years of experience in data analysis and team handling - Solid understanding of panel data, reporting structures, and research definitions - Proven experience working with large datasets — household panel data experience strongly preferred - Comfort handling client ad hoc requests independently, with minimal hand-holding - Demonstrated ability to lead, coach, or mentor others (formally or informally) - Strong written and verbal communication skills - Advanced proficiency in Excel and PowerPoint (or Google Sheets/Slides equivalents) - Strong data storytelling ability — turning numbers into clear, client-ready narratives - High attention to detail with the ability to manage multiple priorities under deadlines

• Design, develop, and deploy chatbots and voice bots utilizing leading Conversational AI platforms such as Microsoft Bot Framework, Google CCAI, Dialogflow CX. • Craft clean, efficient, and maintainable code adhering to industry best practices and standards. • Develop custom components and tools to optimize the functionality and performance of our chatbot ecosystem. • Collaborate closely with developers, designers, and other stakeholders to meet project requirements and user expectations. • Leverage natural language processing (NLP), LLM and machine learning (ML) techniques, including TTS, STT, and SSML, to enable our chatbots to comprehend and respond intelligently to user inputs. • Integrate chatbot systems seamlessly with backend systems, databases, and APIs to facilitate smooth data exchange and interactions. • Investigate and resolve complex technical issues by analysing logs and debugging code for continuous improvement. • Stay ahead of the curve by keeping up-to-date with the latest trends and advancements in chatbot development.

• Architect, build, and maintain scalable ETL/ELT pipelines on the Databricks Lakehouse Platform using PySpark, Spark SQL, and Delta Lake. • Design and implement medallion (bronze/silver/gold) data architectures and enforce data quality, governance, and lineage standards. • Optimize Spark jobs and cluster configurations for performance and cost, including partitioning, caching, and autoscaling strategies. • Implement and manage Unity Catalog for access control, data governance, and cross-workspace asset sharing. • Build and orchestrate workflows using Databricks Workflows, Delta Live Tables, and CI/CD pipelines. • Collaborate with data scientists, analysts, and business stakeholders to translate requirements into reliable data products. • Establish engineering best practices, conduct code reviews, and mentor junior data engineers. • Monitor production pipelines, troubleshoot failures, and drive root-cause analysis and continuous improvement.

• Design, develop, and maintain scalable data pipelines and ELT/ETL workflows on Snowflake, integrating data from diverse internal and external sources. • Architect and optimize Snowflake data models, schemas, and warehouses for performance, reliability, and cost efficiency. • Implement and enforce data governance, security, role-based access controls, and data quality standards across the platform. • Monitor and tune warehouse performance, query execution, and resource consumption to control costs and meet SLAs. • Build and maintain CI/CD pipelines for data infrastructure using tools such as dbt, Git, and orchestration frameworks (e.g., Airflow). • Leverage advanced Snowflake features — Snowpipe, Streams, Tasks, Time Travel, Dynamic Tables, and Snowpark — to deliver near-real-time and automated data solutions. • Collaborate with analysts, data scientists, and business stakeholders to translate requirements into robust data solutions. • Mentor junior engineers, conduct code reviews, and establish best practices for data engineering across the team.