✨ AI Summary
The Senior Data Analyst / Data Engineer will be responsible for designing, building, and optimizing ETL/ELT data pipelines from various sources, maintaining cloud data warehouses and data lakes, and implementing data governance. This role involves querying large datasets using SQL and Python to extract business value and creating automated dashboards and BI reports using Tableau or Power BI.
The ideal candidate will have 4-6+ years of combined experience in data engineering and advanced data analysis, with advanced proficiency in SQL, Python, or Scala. Experience with cloud platforms like AWS, GCP, or Azure, and familiarity with Spark or Hadoop are required. Expertise in Power BI or Tableau, and hands-on practice with tools like Airflow or dbt are also essential. A Bachelor of Science degree in Computer Science, Engineering, or Statistics is required.
Design, build, and optimize robust ETL/ELT data pipelines from multiple data sources. Maintain cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and data lakes. Implement data governance, validation checks, and error-handling routines. Query large datasets using complex SQL and Python to extract business value. Create automated dashboards and BI reports (Tableau, Power BI) for stakeholders.
Requirements
- 4 to 6+ years of combined experience in data engineering and advanced data analysis.
- Advanced SQL, Python, or Scala.
- Experience with AWS, GCP, or Azure; familiarity with Spark or Hadoop.
- Expertise in Power BI or Tableau.
- Hands-on practice with tools like Airflow or dbt.
- Degree in Computer Science, Engineering, Statistics
Description
Design, build, and optimize robust ETL/ELT data pipelines from multiple data sources. Maintain cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and data lakes. Implement data governance, validation checks, and error-handling routines. Query large datasets using complex SQL and Python to extract business value. Create automated dashboards and BI reports (Tableau, Power BI) for stakeholders.