Commerce is becoming ever more digital, the way we sell, buy and exchange value is changing faster than ever. Buyers want more convenient ways to buy, pay for products/services, and engage businesses while Sellers want more control over how they sell, manage their business, engage their customers, and collect customer data.
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As a Senior Data Analyst, you will play a key role in developing and implementing our data strategy. You will be responsible for building data pipelines, automating data processing, creating insightful dashboards, and integrating data with our internal tools. Your work will directly impact our ability to understand our business, identify growth opportunities, and improve operational efficiency.
Responsibilities
Data Pipeline Development: Design, build, and maintain efficient and reliable data pipelines to extract data from various sources (including production databases) and load it into a data warehouse for analysis.
Data Processing and Automation: Develop and implement automated processes for data cleaning, transformation, and aggregation. Ensure data quality, consistency, and accuracy.
Dashboard Development: Create interactive and user-friendly dashboards and reports to visualize key performance indicators (KPIs) and other relevant metrics. Provide insights to various teams across the organization to support data-driven decision-making.
Data Integration: Build and maintain pipelines to integrate processed data with internal tools and systems. Ensure seamless data flow and accessibility across the organization.
Data Analysis and Insights: Conduct in-depth data analysis to identify trends, patterns, and opportunities for business improvement. Communicate findings and recommendations to stakeholders in a clear and concise manner.
Collaboration: Work closely with cross-functional teams, including product, engineering, marketing, and operations, to understand their data needs and provide effective solutions.
Database Management: Administer the data warehouse and ensure optimal performance.
Requirements
Proven experience (6+ years) as a Data Analyst, Data Engineer, or similar role.
Strong proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL).
Experience with data warehousing concepts and technologies.
Proficiency in at least one programming language (e.g., Python, R) for data manipulation and analysis.
Experience with data visualization tools (e.g., Tableau, Power BI, Metabase).
Familiarity with ETL processes and tools.
Strong analytical and problem-solving skills.
Excellent communication and presentation skills.
Ability to work independently and as part of a team.
Preferred Qualifications
Experience with cloud-based data warehousing solutions (e.g., BigQuery, Redshift).
Experience with big data technologies (e.g., Hadoop, Spark).
Knowledge of statistical modeling and machine learning techniques.
Experience with data integration tools (e.g., Airflow, Kafka).
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