Job Summary
We are seeking an experienced and highly skilled Senior Data Engineer with deep expertise in Azure Data Factory, Python, SQL Server, ETL development, and Snowflake. The ideal candidate will be capable of independently designing, building, and optimizing large-scale data solutions while playing a key role in architecture, development, and performance tuning across the data ecosystem.
Key Responsibilities
Design, develop, and maintain scalable ETL pipelines using Azure Data Factory and other Azure data services.
Build and optimize data workflows integrating SQL Server, Snowflake, and multiple on-premises and cloud data sources.
Write clean, reusable Python scripts for data transformation, automation, and orchestration.
Develop and maintain complex SQL queries, stored procedures, and functions, including performance tuning.
Implement end-to-end data ingestion, transformation, and integration solutions aligned with business needs.
Manage and optimize Snowflake data warehouse architecture, warehouses, and query performance.
Monitor, troubleshoot, and resolve data pipeline and workflow issues, ensuring high availability.
Enforce data quality, governance, and security best practices across all datasets and pipelines.
Collaborate with cross-functional teams while being able to own deliverables independently with minimal supervision.
Prepare and maintain technical documentation, including design specifications, data flow diagrams, and operational procedures.
Required Skills & Qualifications
8+ years of professional experience in Data Engineering or a related field.
Strong hands-on expertise with Azure Data Factory (pipelines, triggers, mapping data flows, linked services).
Proficiency in Python for scripting, data manipulation, and automation tasks.
Advanced experience with SQL Server (T-SQL) including query tuning and database optimization.
Proven track record in designing and implementing ETL solutions for large-scale systems.
Solid working knowledge of Snowflake (warehouses, schema design, optimization, RBAC roles).
Experience handling structured, semi-structured, and unstructured data.
Ability to work independently, taking full ownership of technical modules and deliverables.
Strong analytical, problem-solving, and communication skills.
Preferred Qualifications
Experience with Azure Databricks or Apache Spark.
Familiarity with DevOps practices, including CI/CD pipelines and Git-based workflows.
Understanding of cloud security, data governance, and compliance standards.
Why Join Us?
Opportunity to work with modern cloud-native and data engineering technologies.
High autonomy and ownership of end-to-end data engineering projects.
A collaborative, innovative, and fast-paced environment with opportunities for career growth.
