Senior Data Engineer

The Senior Data Engineer will serve as a key contributor and technical leader within the Data & Analytics team, responsible for architecting, designing, and developing scalable data pipelines, data models, and ingestion frameworks that power analytics, reporting, and product functionality across the organization's software platform. This role will partner closely with business stakeholders, analytics teams, software engineers, and cloud architects to deliver reliable, high-performance data solutions that support strategic decision-making and operational excellence.

The ideal candidate brings deep expertise in modern cloud-based data platforms, data warehousing, ETL/ELT development, and Azure data services, with a strong focus on scalability, performance, data quality, and governance.

• Design, develop, and maintain scalable and resilient data pipelines supporting batch and near real-time data processing.
• Build and maintain datasets, schemas, and data models within the enterprise data warehouse using Snowflake
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• Architect and implement robust ETL/ELT frameworks to ingest data from diverse internal and external sources.
• Design and optimize dimensional and analytical data models to support reporting, dashboards, advanced analytics, and product features.
• Develop reusable data ingestion patterns and frameworks to accelerate onboarding of new data sources.
• Design, develop, and support data integration solutions using Azure Data Factory (ADF).
• Create and manage data orchestration workflows, pipelines, triggers, and monitoring processes within Azure.
• Integrate data from APIs, databases, SaaS applications, flat files, and streaming sources.
• Leverage Azure services to support scalable, secure, and cost-effective data solutions.

• Develop and optimize Snowflake database objects, including tables, views, tasks, streams, and stored procedures.
• Implement performance tuning strategies to improve query efficiency and warehouse utilization.
• Manage data loading, transformation, and validation processes within Snowflake.
• Ensure adherence to data governance, security, and compliance requirements.

• Implement data validation, monitoring, and reconciliation processes to ensure data accuracy and completeness.
• Troubleshoot and resolve data pipeline failures, performance bottlenecks, and integration issues.
• Establish best practices for logging, alerting, testing, and deployment of data engineering solutions.
• Support data observability initiatives and proactively identify potential data issues.
• Provide technical leadership and mentorship to junior and mid-level data engineers.
• Collaborate with business analysts, data scientists, application developers, and product teams to understand data requirements and translate them into technical solutions.
• Participate in architecture reviews, design discussions, and technology evaluations.
• Contribute to the development and enforcement of data engineering standards, best practices, and documentation.

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related technical field.
• 7+ years of experience in data engineering, data warehousing, or related disciplines.
• 3+ years of hands‑on experience with Snowflake data warehouse development and administration.
• 3+ years of experience developing data integration solutions using Azure Data Factory (ADF).
• Strong proficiency in SQL, data modeling, and database optimization techniques.
• Experience building and maintaining large-scale ETL/ELT pipelines.
• Strong understanding of data warehouse concepts, dimensional modeling, and analytics architecture.
• Experience working with structured, semi-structured, and unstructured data.
• Knowledge of CI/CD practices and source control systems such as Git.
• Strong analytical, problem‑solving, and troubleshooting skills.
• Excellent communication and stakeholder management abilities.

• Experience with Azure cloud services such as Azure Data Lake Storage (ADLS), Azure Functions, Azure Synapse Analytics, Azure Databricks, and Azure Key Vault.
• Experience with Python, PySpark, or other scripting languages used in data engineering.
• Familiarity with data governance, metadata management, and data cataloging tools.
• Experience implementing data quality frameworks and monitoring solutions.
• Knowledge of Agile/Scrum methodologies.
• Snowflake and/or Microsoft Azure certifications preferred.