Python Data Engineer (Data Core Team) at Dealfront

, , Germany -

Full Time

Start Date

Immediate

Expiry Date

29 Dec, 25

Salary

0.0

Posted On

30 Sep, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Data Engineering, AWS, ETL, CI/CD, SQL, Kafka, Redis, Solr, Opensearch, APIs, Data Quality, Monitoring, Logging, Documentation, Team Collaboration

Industry

Software Development

Description

We are a remote-first, international Pipeline Generation Platform for B2B revenue teams. We give businesses the clarity to focus their efforts where they’ll count most - on the accounts that fit their ideal customer profile, show real buying intent, and are actively engaging. No more cold outreach and no more bloated target lists. Just better deals, faster. Our platform brings together powerful data, real-time insights, and intelligent prioritisation to help our customers identify, engage, and convert the right accounts, at the right time. Built for teams that value speed, precision, and simplicity, Dealfront turns complexity into action. Join us and be a part of our journey to transform the way businesses win more deals! Position Overview We are looking for an experienced Python Data Engineer to join our Data Core team. This role combines the strengths of data engineering and Python software development, focusing on designing, building, and maintaining the core data pipelines and infrastructure that power our platform. Being part of the Data Core team, you will actively contribute to architectural discussions, drive best practices in coding and data engineering, and advocate for maintainable, high-quality solutions. You become part of a nice, motivated and skilled team in which everyone pulls together. What you’ll work on Design and implement scalable data pipelines and processing workflows, mainly in Python. Build and maintain integrations between multiple data sources, storage systems, and downstream consumers. Develop APIs and services to support internal data products and applications. Ensure robust CI/CD pipelines for smooth deployment, testing, and version control. Implement data quality checks, monitoring, and logging to guarantee reliability and performance. Contribute to infrastructure evolution and automation, leveraging AWS services (e.g., S3, Glue, Lambda, ECS/EKS, Redshift). Document code, processes, and best practices for maintainability. Share insights and mentor other team members on software engineering, data engineering and cloud best practices. At least 3 years of software development experience, with a strong focus on Python. Hands-on experience with data pipelines, ETL/ELT workflows, and data-centric applications. Solid understanding of AWS cloud services relevant to data engineering (e.g., S3, Glue, Lambda, Step Functions, Redshift, EMR). Good understanding of GIT workflows, CI/CD + working with Unit Tests Solid experience in interacting with technologies such as SQL (especially PostgreSQL), Kafka, Redis, Solr/Opensearch Team player with strong communication skills and the ability to support and improve the work of colleagues. Desired: Experience with a K8s environment and Docker Be physically located within Europe In this role, your contributions will directly influence the future direction and success of our products, shaping their growth and ensuring they meet the evolving needs of our customers. The chance to work with a very knowledgeable, high-achieving and fun team. An international, diverse, dynamic and committed work environment. The opportunity to work remotely, with a flexible work schedule. Mental Health support with Auntie. Annual company retreats in sunny locations and team off-sites :) We value diversity and inclusion in our workplace and welcome applications from candidates across all backgrounds and do not discriminate on the basis of race, religion, gender, sexual orientation, age, marital status, disability or any other protected characteristics.

Responsibilities

Design and implement scalable data pipelines and processing workflows, mainly in Python. Build and maintain integrations between multiple data sources, storage systems, and downstream consumers.