Senior Data Engineer

Senior Data Engineer

flexEngage (formerly flexReceipts) is an innovative, retail technology startup headquartered in Downtown Orlando Florida. The company is a graduate of the prestigious business accelerator YCombinator, and is well funded by strong VC firms, including Bullpen Capital, Point Judith Capital, and Synchrony Financial. 

We are the leading provider of personalized transactional communications for retailers, enabling brands like Under Armour, DXL, Michael Kors, GNC, and 5.11 Tactical, to transform standard transactional touchpoints (receipts, order and ship notifications, packing slips, curbside delivery, order tracking, etc.) into dynamic engagement channels that drive customer loyalty and revenue.

flexEngage is looking for a Senior Data Engineer to enable the team to build data-driven products by providing access to our rich datasets at scale. 

This role will be the first full-time data engineer on the team. The need for the role arises out of a focus to increase the maturity of our products by adding valuable data-driven features. In this role, you will have a significant voice in defining the long-term vision for our approach to data engineering - from setting technology standards to helping build out a team as our products expand.

This role is remote and may be based anywhere in the US. However, the candidate should be aware that most team meetings are mid to late morning (Eastern time) to accommodate team members in Europe. Flexibility on both sides will be encouraged.

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  Empower the organization to build data-driven products by building data processing pipelines that enable easier access to data. 

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  Write maintainable, performant, and cost-efficient code that can be validated with automated tests. 

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  Maintain our data warehouse with timely and quality data.

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  Create and maintain documentation for the systems and repositories you own.

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  Develop features and improvements to flexEngage products.

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  Participate in all aspects of the development process including story grooming, technical design, coding, code reviews, QA, and delivery.

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  Collaborate with Product Management, other engineers, and other stakeholders in the development of new features.

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  Establish data engineering standards for style, maintainability, and best practices. Maintain and advocate for these standards through feature development and code reviews.

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  Identify areas of improvement in the codebase and improve it through your contributions. Drive change by being an advocate for these improvements.

• Bachelor's degree in Computer Science, related degree, or equivalent practical experience.

• 3+ years of hands-on experience deploying production quality code.

• Professional experience using Python for data processing.

• Professional experience implementing ETL best practices at scale.

• Professional experience with data pipeline tools (Airflow).

• Demonstrably deep understanding of SQL and analytical data warehouses (Snowflake preferred).

• Experience using cloud environments (AWS preferred). Experience provisioning infrastructure through code (e.g. Terraform, Cloud Formation, Ansible).

• Experience using CI/CD tools like Bitbucket Pipelines or Jenkins.