Data Engineer

About the Role

We are looking for a Senior Data Engineer with strong Snowflake expertise to design and evolve scalable data solutions on a modern cloud data platform.

You will play a key role in building high‑performance data pipelines, scalable data models and robust governance frameworks using Snowflake capabilities, supporting enterprise analytics, BI and regulatory use cases.

This role operates in a large-scale enterprise environment with complex data and regulatory requirements, contributing to improved data availability, reliability and time‑to‑insight for business and regulatory reporting.

You will work with structured and semi‑structured data, leveraging Snowflake-native features for efficient processing, optimization and scalability.

Key Responsibilities

• Design and evolve scalable ELT pipelines in Snowflake using SQL-based transformations and modern orchestration tools
• Implement and optimize data ingestion frameworks (batch and near real-time) using cloud-native integrations
• Build and maintain data models (raw, staging, core, data marts) aligned with enterprise architecture
• Optimize performance and cost efficiency (query tuning, warehouse sizing, resource monitors)
• Define and promote best practices and standards for Snowflake development
• Review data models and pipelines to ensure quality, scalability and maintainability
• Implement data governance and security (RBAC, data masking, encryption, row-level security)
• Ensure data quality, lineage tracking and integration with metadata/catalog solutions
• Drive orchestration and transformations (Airflow and/or DBT preferred; ADF or similar tools)
• Drive CI/CD pipelines and version control (GitHub) for data platform components
• Monitor pipeline performance, reliability and data quality, implementing observability and alerting where needed
• Collaborate with cross-functional teams (Data Analysts, BI Developers, Data Management) to deliver scalable solutions
• Automate processes and standardize reusable data engineering frameworks
• Maintain clear and structured documentation for pipelines, data models and platform configurations

Required Qualifications

Must-have

• Advanced SQL skills and experience with performance optimization in large-scale data environments
• Hands-on Snowflake experience (data warehousing, ELT, performance tuning, security models)
• Strong background in Data Warehouse design and enterprise data architecture
• Solid understanding of data modeling (dimensional & normalized) and distributed systems
• Experience with orchestration and transformation tools (Airflow, ADF, DBT or similar)
• Experience in cloud environments (AWS / Azure / GCP), ideally integrated with Snowflake
• Experience with data ingestion patterns (ELT, CDC, event-driven pipelines)
• Experience with CI/CD and DevOps practices for data platforms

Nice-to-have

• Experience with semi-structured data (JSON, Parquet, VARIANT)
• Experience with Databricks (PySpark, Delta Lake) in hybrid architectures
• Experience with streaming technologies (Kafka, Kinesis)
• Experience in banking / financial services / regulatory reporting