Senior Snowflake Data Engineer

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If you are excited to work on impactful projects with interesting and diverse clients in North America, Canada, Asia, and Europe - then this might just be the place for you.

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Proactiviti offer competitive pay, training, and benefits.

Salary & Benefits

Our clients in North America.

Who you'll work with

Key Responsibilities:

Data Platform Design and Development:Design, develop, and maintain data pipelines and architectures on Microsoft Azure and Snowflake.
Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and build solutions that meet those needs.
Implement best practices for building scalable, efficient, and secure data platforms to process and store large volumes of structured and unstructured data.
Build and maintain cloud-based data warehouses and data lakes, ensuring seamless integration with other services.
SQL, DBT, and Snowflake Expertise:Write complex, optimized SQL queries for data extraction, transformation, and analysis.
Design and implement DBT (Data Build Tool) models to support efficient transformation workflows.
Work extensively with Snowflake, managing the integration, optimization, and scaling of data within the platform.
Develop and implement Snowflake best practices for database management, security, and scalability.
Data Modeling and Performance Tuning:Utilize advanced data modeling techniques to design logical, physical, and dimensional data models that meet business requirements.
Tune and optimize database queries, ensuring performance improvements in Snowflake and other platforms.
Identify and resolve performance bottlenecks across the data pipeline, from ingestion to transformation and storage.
Perform data quality checks and monitor pipeline performance, ensuring data is accurate, consistent, and timely.
Cloud Technologies and Microsoft Azure Services:Leverage Microsoft Azure services like Azure Blob Storage, Azure Data Factory, Azure Databricks, and others to architect and implement cloud data solutions.
Manage and monitor cloud resources to ensure optimal performance, scalability, and cost-effectiveness.
Integrate data solutions with various Azure components, ensuring seamless data movement between storage, analytics, and reporting tools.
Collaboration and Stakeholder Engagement:Work closely with cross-functional teams to understand business objectives and deliver data solutions that drive insights and decision-making.
Act as a mentor to junior team members, providing guidance and best practices for data engineering, SQL development, and Snowflake usage.
Collaborate with DevOps, cloud engineers, and data analysts to integrate data systems with applications and reporting platforms.
Automation and Data Pipeline Management:Automate data extraction, transformation, and loading (ETL) processes to streamline the movement and transformation of data.
Implement monitoring, logging, and alerting systems to track the performance and health of data pipelines.
Ensure data governance, security, and compliance standards are met throughout the data pipeline lifecycle.
Troubleshooting and Issue Resolution:Proactively identify and resolve issues with data processing, storage, and retrieval.
Perform root cause analysis for performance issues and optimize processes accordingly.
Collaborate with IT and other teams to address infrastructure or data-related challenges and implement effective solutions.

What you'll do

6+ years of experience in data engineering or related fields with hands-on experience in SQL, DBT, Python, and Snowflake.
Strong expertise in SQL and DBT, including writing optimized queries, transformations, and data modeling.
Extensive experience with Snowflake for managing large-scale data warehouses, including data loading, transformation, and optimization.
Proficiency in Python for writing data pipelines, automation scripts, and integrations with cloud-based tools and services.
Familiarity with data modeling techniques, including star schema, snowflake schema, and dimensional modeling.
Experience with Microsoft Azure services such as Blob Storage, Azure Data Factory, Azure Databricks, and others for data integration and processing.
Hands-on experience with data pipeline orchestration, automation, and performance tuning in cloud environments.
Strong understanding of cloud data platforms, data lakes, and data warehouses, specifically Snowflake and Azure-based services.
Knowledge of security and data governance best practices within cloud environments.
Excellent problem-solving skills and a deep understanding of performance tuning techniques.
Ability to work collaboratively in cross-functional teams and effectively communicate with technical and non-technical stakeholders.

Preferred Skills:

Experience with Azure Synapse Analytics, Azure SQL Database, or other related Azure analytics services.
Familiarity with data visualization tools such as Power BI, Tableau, or similar.
Experience with containerization and orchestration tools like Docker and Kubernetes.
Familiarity with DevOps practices and CI/CD pipelines for data workflows.
Experience with Apache Spark, Hadoop, or other big data technologies.

Qualifications

Role Description

You will work on building robust, scalable, and high-performance data solutions, ensuring that data pipelines, storage, and platforms meet both business needs and technical requirements. Your expertise in data modeling, performance tuning, and leveraging cloud technologies like Microsoft Azure services such as Blob Storage will be critical to driving the success of our data initiatives.