Design and develop ETL/ELT processes using Azure Data Factory for data ingestion, transformation, and storage (SQL Server and Snowflake)

Optimize and maintain data pipelines across cloud (Azure) and on-premise environments

Develop, schedule, and monitor batch and real-time data pipelines to ensure reliability

Design and optimize SQL Server and Snowflake schemas, including tables, indexes, and partitions

Write and optimize PL/SQL and T-SQL scripts for data transformation, cleansing, and loading

Ensure data integrity, consistency, and security across all data platforms

Monitor data pipelines for failures and performance issues, resolving problems promptly

Automate error-handling and data reconciliation to enhance pipeline robustness

Collaborate with Data Analysts, BI teams, and stakeholders to meet data requirements

Maintain detailed documentation of data flows, transformation logic, and pipeline configurations

Participate in code reviews and uphold data engineering best practices

Work closely with product owners and business teams to align data solutions with business needs

3+ years of experience in data engineering, ETL development, or data transformation roles

Hands-on experience designing and maintaining large-scale ETL/ELT pipelines in cloud environments

Strong expertise in Azure Data Factory, SQL Server, and Snowflake

Advanced skills in PL/SQL and T-SQL for data transformation and performance tuning

Experience in ETL development, data warehousing, and data modeling

Knowledge of cloud-based data architectures, specifically Azure, and database administration

Strong analytical and problem-solving skills

Ability to work autonomously and collaborate effectively with BI, PO, and business teams

Detail-oriented with a focus on data quality and performance optimization

Upper-Intermediate English proficiency (B2 level)