Senior Data Analyst

We are seeking a dedicated and experienced Senior Data Analyst with an engineering background to join our team. This role involves managing and interpreting complex data sets to provide critical insights, supporting decision-making processes. As a Senior Data Analyst, you are expected to have a profound understanding of complex ETL pipelines, data manipulation and data analysis, strong problem-solving and analytical skills, as well as excellent communication and presentation skills.

You should be able to identify trends and develop strategies for leveraging data to improve business outcomes. Additionally, you should be able to collaborate with other team members and stakeholders to ensure that all data strategies are properly implemented.

1. Streamlining and optimizing data extraction, preparation, and transformation processes while maintaining its integrity and accuracy.
2. Leveraging SQL (BigQuery) for the development and execution of data queries.
3. Utilizing Python scripting for advanced data manipulation and analysis tasks.
4. Analyzing, interpreting, and visualizing large complex datasets, transforming raw data into actionable insights that influence business decisions.
5. Collaborating with cross-functional teams to assist in integrating data analytics into ongoing business strategies and objectives.
6. Identifying key business trends and patterns from complex data sets, disseminating these insights across the company to drive decision-making.
7. Engaging in rigorous testing and validation of data sets to ensure accuracy and consistency.
8. Providing expertise on statistical analysis and data mining techniques to address the company’s needs.
9. Exploring new ways to enhance data quality and usability, with a focus on continuous improvement.  
10. Leading initiatives for data integrity and normalization, maintaining the company's data architecture.
11. Collaborating with management to prioritize business and information needs.
12. Locating and defining new process improvement opportunities.

1. Degree in Mathematics, Computer Science, Statistics, or a related field.
2. Proven working experience as a data analyst, data engineer, or business data analyst.
3. Proficiency in SQL; Including Functions, Procedures, and Performance Optimization, With a Deep Understanding of Database Design. Experience with BigQuery will be considered a plus.
4. Proficiency in designing, building, and maintaining complex ETL pipelines using various tools and platforms. Experience with Dataform will be considered a plus.
5. Experience with APIs to extract and integrate data from external sources.
6. Proficiency in Python; knowledge of other programming languages will be considered a plus.
7. Experience with NoSQL databases and various other data formats (XML, JSON, etc.).
8. Profound knowledge of statistics.
9. Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
10. Experience of using visualization tools (Apache Superset, Looker Studio, Looker, Tableau, etc.).
11. Ability to think creatively and come up with innovative solutions.
12. Excellent organizational and communication and presentation skills.

Preferred Additional Qualifications:

1. Experience of using Google Cloud Platform products.
2. Experience of building data pipelines with Dataform and BigQuery
3. Experience of working with version control (GIT)
4. A working knowledge of financial analysis.
5. An understanding of web technologies.
6. Experience of working with a SaaS business.
7. A working knowledge of ML models, especially classification and anomaly detection models.
8. Advanced knowledge of Google Analytics and other web analytics services.
9. Experience of working with Google Tag Manager.
10. Experience working with Ads platforms, such as Google Ads, Meta Ads, etc.
11. Knowledge of DevOps practices and tools, including containerization (Docker) and basic CI/CD pipelines.
12. Experience with Apache Superset.