Jetzt als Data Engineer (f/m/d) durchstarten – Bei Taktile GmbH in Berlin

Taktile exists to create value for organizations through smarter and safer decisions at scale. Our goal is to become the world's leading software provider for automated decision-making in the financial services industry and, to date, our software has been used by our customers to power over 1,000,000 critical business decisions every day.

• Taktile is based in Berlin, London and New York City.
• Taktile was founded by machine learning and data science veterans with extensive experience building and running production ML in financial services.
• Our team consists of engineers, entrepreneurs, and researchers with a diverse set of backgrounds. Some of us attended top universities such as Harvard, Oxford, and Stanford and some of us have no degree at all.
• Our team has accumulated extensive work experience at leading tech companies such as Google, Amazon, and Meta, startups, and the enterprise software sphere
• Our backers include Y Combinator, Index Ventures, and stellar angels such as the founders of Looker, GitHub, Mulesoft, Datadog, and UiPath.

We’re backed by some of the world’s leading investors and show great traction with scale-ups and large enterprises across the financial services and insurance industry. We are looking to build on this success by growing our sales team, professionalizing our go-to-market, and acquiring more customers.

That’s where you come in.

At Taktile, data is our lifeblood. As a Data Engineer embedded in the go-to-market team, you'll be at the heart of our drive to meet ambitious growth targets. Your mission? Crafting data sets, metrics, and automations that empower our Business Development and Marketing teams. Armed with both technical know-how and business acumen, you spearhead our move toward a scalable, data-driven go-to-market motion at Taktile.
If you are passionate about building data products that solve real business problems, boast a rock-solid foundation in Python and SQL, and thrive in a collaborative environment that nurtures personal and professional development, then we believe this role is tailor-made for you!

ABOUT YOU

• You’re a tech-savvy and business-focused individual, which means that you care deeply about the underlying business problem and enjoy developing technical solutions that yield tangible impact.
• You’re excellent at implementing automation scripts and data pipelines in Python.
• You feel very comfortable navigating and deploying models and data pipelines within a cloud-native data stack (think Lambda, S3, DBT, Snowflake)
• You have an ownership mindset and you excel at engaging stakeholders throughout the entire process - from defining initial requirements to implementation and beyond, actively seeking feedback for ongoing enhancements.
• You’re a humble individual with a growth mindset, exhibiting eagerness to acquire new skills, embrace emerging methodologies, and integrate best practices into our operations.
• You have exceptional written and verbal communication skills in English.

• Data Pipeline Development: Design, develop, and maintain robust and scalable data pipelines to efficiently load data from diverse sources into our data warehouse.
• Data Modeling: Engage with stakeholders to deeply understand data requirements and collaboratively craft dimensional data models that not only meet these needs but also deliver tangible business value.
• Data Activation: Spearhead the creation of lightweight automations and intuitive dashboards, empowering business stakeholders to derive immediate actionable insights from the data.
• Collaboration: Forge strong collaborative relationships with cross-functional teams, including software engineers, product managers, and commercial stakeholders, ensuring alignment on data initiatives and driving collective success.
• Documentation: Produce and uphold comprehensive documentation for data engineering processes, data models, and system architecture, fostering transparency and facilitating knowledge sharing across the organization.
• Continuous Learning: Remain at the forefront of industry trends, emerging technologies, and best practices in data engineering. Apply this knowledge proactively to enhance and evolve our data infrastructure, keeping it agile and future-proof.

• Experience with Docker and other DevOps tools like CI/CD, Terraform, etc.
• Exposure to Machine Learning and statistical modeling.
• Domain expertise in sales and marketing or the financial services industry.