Data Engineer
Job Description
About the role:
We’re looking for a skilled Data Engineer with deep Snowflake expertise to help modernize and
scale our data platform. If you thrive in a fast-moving environment, can wrangle messy pipelines,
and want to build the backbone of a cloud-first data strategy, this role is for you. You’ll work across
legacy and modern systems to deliver reliable, high-quality data to customers.
Responsibilities
• Design, build, and maintain scalable and efficient data pipelines to support analytics,
reporting, and operational use cases
• Collaborate closely with product owners, analysts, and data consumers to translate business
requirements into reliable data solutions
• Develop and maintain data integration workflows across both cloud-native and on-premises
systems
• Champion best practices in data architecture, modelling, and quality assurance to ensure
accuracy and performance
• Participate in sprint planning, daily stand-ups, and retrospectives as an active member of a
cross-functional agile team
• Identify and remediate technical debt across legacy pipelines and contribute to the
modernization of the data platform
• Implement robust monitoring and alerting for pipeline health, data quality, and SLA
adherence
• Write and maintain documentation for data flows, transformations, and system
dependencies
• Contribute to code reviews and peer development to foster a collaborative and high-quality
engineering culture
• Ensure adherence to security, privacy, and compliance standards in all data engineering
practices
Skills & Qualifications
• 5+ years of professional experience in data engineering, analytics engineering, or related
fields
• Bachelor’s degree in computer science, or equivalent field and 2+ years of experience
• Advanced SQL skills, including performance tuning and query optimization
• Expertise in Snowflake, including data warehousing concepts, architecture, and best
practices
• Experience with modern data transformation tools (e.g., dbt)
• Experience building and maintaining automated ETL/ELT pipelines, with a focus on
performance, scalability, and reliability
• Proficiency with version control systems (e.g., Git), working within CI/CD pipelines and
experience with environments that depend on infrastructure-as-code
• Experience writing unit and integration tests for data pipelines
• Familiarity with data modeling techniques (e.g., dimensional modeling, star/snowflake
schemas)
• Experience with legacy, on-premise databases such as Microsoft SQL Server is preferred
• Exposure to cloud platforms (e.g., AWS, Azure, GCP), cloud-native data tools, and data
federation tools is a plus
• Experience with Sql Server Reporting Services (SSRS) is beneficial