Data Analyst

The Data Analyst is responsible for analyzing data to identify insights, trends, and patterns, and communicating findings clearly through effective storytelling. The role works independently to ensure data accuracy, turn unclear requests into clear tasks, and proactively manage timelines while collaborating with stakeholders. Data Analyst also partners with business and cross-functional teams to ensure analytics efforts support overall business objectives

• Perform exploratory data analysis to uncover insights, trends, and patterns. Analyze data, generate and present actionable insights based on hypotheses with minimal guidance. Have strong storytelling skills to deliver messages to the audience.
• Apply basic statistics and machine learning techniques (e.g., regression, clustering) to draw conclusions and improve models.
• Write efficient, readable, and optimized SQL querieson columnar data warehouses like Snowflake and BigQuery. Write SQL on modeling tools such as dbt, apply dimensional modeling concepts and distinguish between data warehouse and data mart.
• Script in Python to derive business insights and automate data processing for decision-making. If required, do scheduling with tools like Airflow.
• Deliver visualization using tools and libraries such as Metabase, Tableau, Seaborn, etc. Select the appropriate visualization for specific purposes.
• Utilize product analytics to decide on direct analysis or building models from tracked data.
• Clarify and prioritize requests based on impact/effort, proactively communicate timeline and raise blockers, and validate urgency to avoid delays. Collaborate with cross-functional teams to align analytics efforts with business objectives.
• Communicate clearly with both technical and non-technical audiences, contribute to team initiatives, document context, seek feedback, and review peers' work.

• Bachelor's or Master's degree in a related field and 3-5 years of experience in data analysis or business analytics.
• High curiosity in data, analytics, and business in general.
• Strong skills in writing efficient and readable SQL queries, and familiarity with Snowflake, BigQuery, and dbt.
• Proficiency in Python for data processing, automation, and experience with scheduling tools like Airflow.
• Proficient with data visualization tools such as Metabase, Tableau, and Seaborn, and strong ability to convey insights effectively.
• Excellent communication and collaboration skills with both technical and non-technical stakeholders, including clear written and verbal communication.
• Ability to work independently, ensuring data accuracy, resolving data issues, and proposing improvements within the scope of work.
• Proactively communicate, clarify requests to minimize back-and-forth revisions, prioritize tasks based on impact and effort, and raise blockers to avoid delays.
• Have a growth mindset. Actively seek feedback, contribute opinions, suggestions, and documentation, and start reviewing peers' work, participating in team initiatives and processes.