Senior Data Analyst

• Interpret data, analyze results, and apply statistical techniques.
• Develop and implement data analyses, data collection systems, and strategies to optimize efficiency and statistical quality.
• Obtain data from primary or secondary sources and maintain databases.
• Implement database security routines and protocols.
• Establish best practices for data administration procedures within the SME environment.
• Build data extraction pipelines from multiple sources and store data in a Data Lake using Python, Apache Airflow, and Data Factory.
• Support and monitor the client's data platform.
• Install, configure, and keep database management systems, services, and administration interfaces up to date.
• Verify database environment compliance, including high availability, relational integrity, backup integrity, and vulnerabilities.
• Test and monitor database performance, tune environments, plan capacity, and manage access levels to ensure information security.

• Bachelor's degree preferred, ideally in Computer Science, Engineering, or another data-related field.
• Certification is not required.
• Experience in data-related roles using agile methodologies.
• Experience with conceptual, logical, and physical data modeling, including enterprise, relational, and multidimensional models.
• Maintain and version all developed scripts.
• Advanced SQL proficiency, including Stored Procedures, Views, Indexing, Partitioning, and Query Tuning.
• Experience with modern Data Warehouses and columnar databases, such as BigQuery, Snowflake, Amazon Redshift, or ClickHouse.
• Practical knowledge of cloud providers such as AWS, Azure, or Google Cloud.
• Familiarity with ETL/ELT processes and tools such as Airflow, dbt, ADF, Data Factory, or SSIS.
• Basic knowledge of Python, with a focus on Pandas and NumPy.

• Health Insurance
• Dental Insurance
• Life Insurance
• Meal or Food Allowance
• Transportation Allowance
• Wellhub (formerly Gympass)