Data Engineer

Key Skills: Snowflake, Python, DBT, ETL, GCP, Bigquery, Databricks, Airflow, SQL, Azure, AWS, Redshift

Roles and Responsibilities:

• Design, develop, and maintain scalable batch and data integration pipelines for wealth management datasets.
• Build and manage data models and transformation workflows using dbt and cloud data warehouse technologies.
• Develop Python-based data engineering utilities, validation processes, and automation.
• Configure and support managed data ingestion using Fivetran or Airbyte.
• Implement data quality checks, troubleshoot pipeline issues, and improve reliability across production workflows.

Skills Required:

• 2-10 years of relevant data engineering experience; immediate joiners and candidates with wealth management domain experience are preferred.
• Hands-on experience with Snowflake, BigQuery, or Amazon Redshift.
• Practical experience building transformations and data models with dbt.
• Experience with Fivetran or Airbyte for data ingestion and source integration.
• Strong Python programming skills for data pipelines and engineering automation.

Good to Have:

• Experience with SQL, Apache Airflow, Databricks, AWS, Azure, or Google Cloud Platform.

Education: B.Tech or B.E. in Computer Science, Information Technology, Engineering, or a related discipline.