Job Summary
Job Summary: We're seeking a highly motivated and detail-oriented individual to join our dynamic team as an Entry Level Data Analyst. As a key member of our analytics team, you will play a crucial role in transforming raw data into actionable insights, contributing to informed decision-making across the organization. This entry-level position reports to the Data Analytics Manager and offers a fantastic opportunity for professional growth in the field of data analysis, with clear mentorship and progression paths.
Responsibilities
Job Summary: We're seeking a highly motivated and detail-oriented individual to join our dynamic team as an Entry Level Data Analyst. As a key member of our analytics team, you will play a crucial role in transforming raw data into actionable insights, contributing to informed decision-making across the organization. This entry-level position reports to the Data Analytics Manager and offers a fantastic opportunity for professional growth in the field of data analysis, with clear mentorship and progression paths.
Responsibilities
- Reporting & Collaboration: Report directly to the Data Analytics Manager (day-to-day tasks may be supervised by a Senior Data Analyst). Work closely with Product, Marketing, Finance, and Operations teams to translate business questions into analytical approaches and deliverables.
- Data Collection and Cleaning: Collect, clean, and preprocess large datasets from relational databases and external sources. Implement reproducible data-cleaning routines and contribute to data ingestion/ETL processes under guidance.
- Analysis and Interpretation: Conduct exploratory and statistical analyses to identify trends, patterns, and correlations. Produce clear, action-oriented interpretations of results that support business decisions.
- Deliverables: Produce and maintain weekly operational dashboards (Tableau or Power BI) and monthly performance reports for stakeholders; deliver ad-hoc analyses and presentation-ready slide decks; develop data validation scripts and automated quality checks to ensure reliability of reported metrics.
- Tools and Technologies: Utilize SQL (e.g., Postgres, Redshift, Snowflake) for data extraction; Python (pandas, numpy) and Jupyter notebooks for analysis; Excel (pivot tables, advanced functions) for quick analysis; visualization tools such as Tableau or Power BI for dashboards. Use Git for version control. Familiarity with DBT, Airflow, or cloud data warehouses is a plus.
- Database Management & Documentation: Assist in maintaining and updating team datasets and internal data dictionaries. Document data sources, transformation logic, and metric definitions in Confluence or similar knowledge base to ensure reproducibility and clarity.
- Problem Solving & Quality Assurance: Identify and troubleshoot data-related issues, propose solutions, and implement fixes or escalate appropriately. Ensure deliverables meet agreed SLAs and data quality standards.
- Continuous Learning & Improvement: Stay abreast of industry trends, best practices, and emerging technologies in data analysis. Suggest process improvements for analytics workflows and participate in knowledge-sharing within the team.
- Education: Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field.
- Technical Skills: Proficiency in data analysis tools such as SQL, Python, or R. Strong Excel skills are essential.
- Analytical Thinking: Ability to approach problems analytically, with a keen eye for detail and a commitment to delivering accurate results.
- Communication Skills: Excellent verbal and written communication skills to convey complex findings in a clear and understandable manner.
- Team Player: Collaborative mindset with the ability to work effectively in a team-oriented environment.
- Adaptability: Willingness to learn and adapt to new tools, technologies, and methodologies in the rapidly evolving field of data analysis.
- Problem-Solving: Strong problem-solving skills with a proactive approach to addressing challenges.
- Attention to Detail: Meticulous attention to detail to ensure data accuracy and reliability.