✨ AI Summary
This role involves designing, building, and optimizing robust ETL/ELT data pipelines, maintaining cloud data warehouses and data lakes, and implementing data governance and validation checks. The Senior Data Analyst / Data Engineer will query large datasets using complex SQL and Python to extract business value, and create automated dashboards and BI reports using Tableau or Power BI.
Key requirements include 4 to 6+ years of combined experience in data engineering and advanced data analysis, proficiency in advanced SQL, Python, or Scala, and experience with cloud platforms like AWS, GCP, or Azure. Familiarity with Spark or Hadoop, expertise in Power BI or Tableau, and hands-on practice with orchestration tools like Airflow or dbt are also essential. A degree in Computer Science, Engineering, or Statistics is required.
Requirements
Experience: 4 to 6+ years of combined experience in data engineering and advanced data analysis.Programming: Advanced SQL, Python, or Scala.Big Data & Cloud: Experience with AWS, GCP, or Azure; familiarity with Spark or Hadoop.BI Tools: Expertise in Power BI or Tableau.Orchestration: Hands-on practice with tools like Airflow or dbt.Education: Degree in Computer Science, Engineering, Statistics
Description
Data Engineering: Design, build, and optimize robust ETL/ELT data pipelines from multiple data sources.Architecture & Storage: Maintain cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and data lakes.Data Quality: Implement data governance, validation checks, and error-handling routines.Advanced Analytics: Query large datasets using complex SQL and Python to extract business value.Visualization & Reporting: Create automated dashboards and BI reports (Tableau, Power BI) for stakeholders.