Senior Data Engineer - Snowflake

Data Architecture & Platform Development • Design, architect, and implement scalable data solutions using the Snowflake platform, including data warehousing, data lakes, and hybrid architectures • Develop and maintain robust data pipelines that integrate Oracle databases with Snowflake, ensuring efficient data movement and transformation • Optimize Snowflake features including materialized views, streams, tasks, and resource monitors to maximize performance and cost-efficiency • Establish and maintain data integration patterns between Oracle sources and Snowflake using appropriate tools (Informatica) and methodologies (CDC, batch processing, real-time streaming) Data Engineering & Pipeline Development • Collaborate with cross-functional teams including data scientists, analysts, business stakeholders, and product managers to understand and document data requirements • Design and develop efficient, reliable ETL/ELT data pipelines ensuring data quality, integrity, and security throughout the entire data lifecycle • Implement data validation, monitoring, and alerting mechanisms to proactively identify and resolve data quality issues • Build automated data workflows and orchestration processes to minimize manual intervention and ensure timely data availability Technical Expertise & Best Practices • Demonstrate strong expertise in data modelling including dimensional modelling, data vault, and normalization techniques appropriate for both OLTP and OLAP systems • Perform data wrangling, cleansing, and transformation to prepare data for analytical and operational use cases • Conduct performance tuning and optimization of SQL queries, stored procedures, and data pipelines in both Oracle and Snowflake environments • Implement data governance, access controls, and security best practices including role-based access control (RBAC), data masking, and encryption Analytics & Advanced Applications • Support data analytics initiatives by creating optimized data models and aggregations that enable efficient reporting and analysis • Collaborate with data science teams to prepare and structure data for machine learning workflows, including feature engineering and model deployment pipelines • Develop and maintain documentation for data models, pipeline architectures, data dictionaries, and operational procedures Technical Skills • Expert-level proficiency in SQL with demonstrated experience writing complex queries, optimizing performance, and working with large datasets • Strong hands-on experience with Snowflake platform including SnowSQL, Snowpipe, Streams, Tasks, and Time Travel features • Proficiency in Python for data engineering tasks (bonus: experience with libraries such as pandas, SQLAlchemy, Snowflake Connector) • Familiarity with version control systems (Git) and CI/CD practices for data pipelines Soft Skills • Strong analytical and problem-solving abilities with attention to detail • Excellent communication skills with ability to translate technical concepts for non-technical stakeholders • Ability to work collaboratively in cross-functional teams and manage multiple priorities • Self-motivated with a continuous learning mindset to stay current with emerging technologies