Assembling large, complex data sets that meet business requirements.
Designing and implementing data pipelines for efficient data extraction, transformation, and loading (ETL).
Building and maintaining data infrastructure to ensure data reliability and quality.
Developing analytical tools to provide actionable insights into business performance metrics.
Collaborating with stakeholders including data scientists, product teams, and executives to support data-related technical issues
Proficiency in programming languages such as Python, SQL, and Java.
Experience with data engineering tools like AWS, Azure, Snowflake, and Databricks.
Strong analytical skills to interpret trends and patterns in data.
Knowledge of data modeling and machine learning methods.
Attention to detail and excellent organizational skills