Data Engineer

As a Data Engineer, you will help our company solve its most challenging problems and drive decisions with data. You will work in the Enterprise Data Intelligence team, migrating, acquiring, maintaining, and evolving our data integration process and platform. Responsibilities include data acquisition, design & implementation of ETL/ELT pipelines, database design, job suite execution, monitoring, testing, troubleshooting, and system analysis. You will collaborate with departments to build end‑to‑end data infrastructure that supports reporting and advanced analytics.

Expected pay range: $145,000 – $155,000 (variations based on experience, qualifications, geographic location, and internal equity).

• Design, build, and maintain cloud‑native data pipelines and infrastructure to support analytics, reporting, and data science use cases in a SaaS‑based environment.
• Perform all stages of the data lifecycle: requirements gathering, design, ingestion, transformation, modelling, testing, deployment, monitoring, and production support.
• Implement and manage ELT pipelines using tools such as Fivetran, dbt, and Python, delivering reliable and scalable data solutions.
• Develop and maintain data models, data marts, APIs, and automation scripts to streamline analytics workflows.
• Design and deploy database schemas, tables, and views in Snowflake across multiple environments (DEV, QA/UAT, PROD).
• Collaborate with stakeholders to translate business requirements into robust technical designs.
• Support documentation, training, and enablement to drive adoption of enterprise data assets.
• Protect the data pipeline: monitor the production schedule, troubleshoot failures, and ensure smooth operation.
• Monitor data quality and find solutions to problems when they arise.
• Administer Snowflake security strategy and database management.
• Fine‑tune and optimise databases, queries, and pipelines for improved performance and efficiency.
• Proactively identify processes for system automation to improve team effectiveness and operating efficiencies.
• Research and test new technology solutions, assist in vetting architectural changes, and determine impacts.
• Follow documented procedures for configuring, maintaining, upgrading, testing, and deploying as a database administrator; ensure best technical practices.

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related technical disciplines.

• 5+ years as a Data Engineer in cloud‑native and SaaS‑based environments, supporting enterprise data platforms built on data warehouses, data lakes, and application databases (e.g., Snowflake, Oracle, SQL Server).
• 5+ years of SQL experience with proven ability to write, optimise, and maintain complex queries and stored procedures.
• Programming experience in Python, Scala, or other scripting languages for automation, data transformation, and integration.
• Hands‑on experience designing, building, and maintaining ELT/ETL data pipelines, dimensional models, and data marts using tools such as dbt, Fivetran, or equivalent cloud‑based frameworks.
• Demonstrated experience working with SaaS data sources and APIs, integrating data from cloud‑based systems such as ERP (e.g., Net Suite), CRM, and planning tools (e.g., Oracle EPM, O9, or Salesforce).
• Exposure to or hands‑on experience with AI/LLM frameworks (e.g., Snowflake Cortex, MCP, or similar technologies) to enhance automation and data intelligence.
• Experience with integration and orchestration tools (e.g., Dell Boomi, Airflow, Azure Data Factory, or equivalents).
• Strong understanding of data governance, observability, lineage, and data quality management in a cloud environment.
• Experience with Git‑based version control systems (e.g., Git Hub, Git Lab) and CI/CD workflows for deployment across multi‑environment pipelines (DEV, QA, PROD).
• Working knowledge of cloud platforms (preferably Azure, with exposure to AWS or GCP) and secure data exchange mechanisms (APIs, SFTP).
• Excellent communication and collaboration skills, with the ability to work cross‑functionally in a distributed SaaS organization.

• Master’s degree in Computer Science, Engineering,…