Senior Data Engineer

About Cloudfactory

At Cloud Factory, we are a mission-driven team passionate about unlocking the potential of AI to transform the world.

By combining advanced technology with a global network of talented people, we make unusable data usable, driving real-world impact at scale.

More than just a workplace, we're a global community founded on strong relationships and the belief that meaningful work transforms lives.

Our commitment to earning, learning, and serving fuels everything we do as we strive to connect one million people to meaningful work and build leaders worth following.

Our Culture

At Cloud Factory, we believe in building a workplace where everyone feels empowered, valued, and inspired to bring their authentic selves to work. We are:

• Mission-Driven: We focus on creating economic and social impact
• People-Centric: We care deeply about our team's growth, well-being, and sense of belonging
• Innovative: We embrace change and find better ways to do things together
• Globally Connected: We foster collaboration between diverse cultures and perspectives
• If you're passionate about innovation, collaboration, and making a real impact, we'd love to have you on board!

Role Summary

As a Senior Data Engineer, you will own and evolve Cloud Factory's data platforms, pipelines, and analytical foundations, transforming complex, multi-source data into reliable, business-ready datasets.

You will work business-first, partnering closely with product, operations, and leadership teams to define metrics, design scalable data models, and ensure high standards of data quality, governance, and performance.

By driving modern data engineering best practices, mentoring teammates, and proactively improving our data ecosystem, you will enable confident, data-driven decision-making across the organization.

Responsibilities

• Design, build, and maintain scalable data pipelines and analytics architecture across cloud and on-prem environments
• Develop reliable analytical data models that transform raw data into business-ready datasets
• Define, implement, and own key business metrics, including semantic layers and supporting data structures
• Ensure high data quality and reliability by identifying inconsistencies, resolving data issues, and improving monitoring and governance practices
• Partner with product, operations, finance, and GTM teams to understand analytics needs and deliver actionable insights
• Manage and optimize data pipeline orchestration, including third-party data ingestions and cost/performance improvements
• Lead end-to-end ownership of major reporting domains, ensuring accuracy, health, and long-term scalability.
• Contribute to data engineering standards, documentation, and best practices
• Mentor junior team members and support a culture of continuous improvement
• Participate in incident response, on-call rotations, and post-mortems, proactively improving system reliability

Requirements

• 3-5+ years of experience in Analytics Engineering or Data Engineering
• Expert-level SQL, including complex queries and performance optimization
• Strong Python skills
• Hands-on experience with dbt for data transformation and modeling
• Solid understanding of analytical data modeling techniques. Experience working with both batch and streaming data
• Experience with Snowflake, Click House, or similar data warehouse technologies
• Hands-on experience with ETL/ELT tools such as Fivetran, Airbyte, Peer DB, or similar
• Experience integrating data from APIs and multiple data sources
• Experience with data orchestration tools, preferably Prefect
• Experience with BI and reporting tools such as Looker, Quick Sight, Grafana, or similar
• Familiarity with AWS services (e. g., S3, ECS/Fargate, SNS/SQS)
• Experience with version control and CI/CD practices in analytics workflows (e. g., Git/Git Hub, Git Hub Actions)
• Strong problem-solving skills and attention to detail
• Ability to work independently and manage multiple priorities in a fast-paced environment
• Strong communication and collaboration skills, with the ability to explain technical concepts to non-technical stakeholders
• Customer-focused mindset and comfort working closely with business teams
• Nice-to-have
• Familiarity with data governance, lineage, and documentation tools (e. g., Data Hub, Great Expectations)
• Experience with Ia C (Terraform, Cloud Formation, etc.)

Benefits

• Great Mission and Culture
• Meaningful Work
• Market competitive salary
• Quarterly variable compensation
• Remote and Home working
• Comprehensive medical cover
• Group life insurance
• Personal development and growth opportunities
• Office snacks and lunch
• Periodic team building and social events
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