Senior Manager, Data Engineering (Finance)

The role

We are building a cross-functional team of analysts and engineers with the mission to bring the modeling and analytical capabilities of our finance organization to the next level.

As a Senior Manager, Data Engineering with HelloFresh, you will support the analytic needs of our Finance organization for HelloFresh. You will play a pivotal role in helping us continue to succeed as the leading global meal kit provider. The Senior Manager, Data Engineering will solve challenging problems using business data to build effective data products, and enable complex analysis and data modeling; core responsibilities include the development and automation of data pipelines.

To succeed in this role you must demonstrate a desire to improve on existing approaches, not be afraid to jump in and get your hands dirty, and most importantly have a passion for data. You should strive to continuously drive improvements on data products and actively lead data engineering strategy to maximize both quality and velocity of our development. You should be able to understand how this role fits into our Finance Analytics organization, how your team delivers value to the business, and implement a strategic vision.

What You Will Do

• Lead by example, and take a hands on approach to data engineering projects; make substantial code contributions, and lead the development of new frameworks and capabilities
• Partner with analytical peers and stakeholders to help develop and continuously refine the strategic and tactical roadmap and maintain focus on high impact activities
• Develop an in-depth understanding of the data infrastructure at HelloFresh, working closely with other Data teams (analysts and data scientists) in order to drive value from our wealth of data
• Play an active role in leading data platforms and infrastructure innovation and strategy
• Develop and maintain effective data engineering process and procedures, and ensure on-time delivery of solutions without sacrificing sustainability and minimizing technical debt
• Actively participate with business stakeholders, ensuring common understanding of data engineering projects and aligned vision solution
• Lead the team in architecture design, inclusive of pipeline architecture & data warehouse architecture
• Lead a team of 3-4 data engineers and analysts, providing mentorship, coaching, and regular feedback
• Ensure effective documentation, solution design, thorough code review, and a high standard of data quality management

What You Bring

• Experience developing ETL and creating pipelines for large datasets. Data visualization and reporting experience a plus
• Experience in implementing best practices for data engineering, such as source control repositories, automated code deployments, data quality frameworks, etc.
• A MS in computer science, engineering, or equivalent software engineering experience
• Experience working with Terraform and administrating infrastructure-as-code
• Experience working with permissions for Snowflake and other databases for roles and users through code deployments
• Collaborative: you can work hand in hand with stakeholders across all functions, financial analysts, data scientists, engineers, and other data professionals to realize the full value of data products
• Sense of ownership: you take responsibility for your projects and pride in your work
• Strategic & critical thinking: you get the smaller and the bigger picture
• Excellent communication skills, both verbal and written
• At least three years experience leading a team of data engineers delivering productionalized and stable solutions/products
• At least seven years of professional experience in Data Engineering. Past experience in Finance and Business Analytics is a plus.
• Highly proficient in Python and SQL. Proficient in PySpark and distributed databases. Ideal candidate has experience with Databricks, Snowflake, Airflow, & other AWS data products such as S3 or Glue

New York Pay Range

$153,600—$192,000 USD

Colorado Pay Range

$138,400—$173,000 USD

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