Python Data Engineer

• Build, maintain, and optimize Python-based data pipelines for market-data use cases.

• Design and implement FastAPI services for data ingestion, transformation, and model-enabled workflows.

• Support ML and agentic systems, including dataset preparation, feature extraction, and LLM-assisted automation.

• Develop prompt-driven and tool-calling workflows integrated into data processing pipelines.

• Collaborate closely with data engineers, analysts, and ML teams to deliver reliable, production-ready solutions.

• Apply best practices in ETL/ELT design, testing, and observability.

• Ensure data quality, documentation, and maintainable code across pipelines and services.

• Contribute to continuous improvement of data engineering standards and practices.

• Strong experience developing with Python, including data processing libraries such as Pandas or PySpark.

• Hands-on experience building APIs and microservices using FastAPI.

• Solid SQL knowledge and experience working with relational databases.

• Understanding of ETL/ELT principles and production data pipelines.

• Familiarity with ML or agentic workflows (e.g., LLM automation, embeddings pipelines, or model-orchestrated tasks).

• Experience using Git and CI/CD workflows.

• Ability to work autonomously while collaborating effectively with cross-functional teams.

Nice to have:

• Experience with cloud platforms such as AWS, GCP, or Azure.

• Familiarity with workflow orchestration tools (Airflow, Prefect, or Dagster).

• Experience with Docker and API integrations.

• Understanding of model lifecycle components such as feature stores and inference flows.

• Exposure to financial market data and APIs (e.g., Bloomberg or Refinitiv).

What about languages?

You will need intermediate to advanced English for clear and effective communication with the team.

How much experience must I have?

We are looking for candidates with at least 3+ years of experience in data engineering or related roles.

Our perks and benefits:

🍔 Every day lunches! (headquarters):

• Vegetarian, vegan, gluten and sugar free options.

• Gourmet meals every Friday with our on-site chef!

⚖️ Flexible working options to help you strike the right balance.

👨🏽‍💻 All the equipment you need to harness your talent (Macbook and accessories).

☕ Snacks and beverages available everyday (headquarters).

🎮 After office events, football, tennis and game nights (headquarters).

• Everyone is welcome to join our football league every Wednesday’s and Friday’s.

• Challenge your teammates to a pool game and win the office’s trophy!

• Tennis courts available for friendly matches.

• You are not a sports person? Don’t worry, we also have chess championships, game and music nights for you to join!

📚 Learning opportunities:

• AWS Certifications (we are AWS Partners).

• Study plans, courses and other certifications.

• English Lessons.

• Learn from your teammates on our Tech Tuesdays!

👩‍🏫 Mentoring and Development opportunities to shape your career path.

🎁 Anniversary and birthday gifts.

🏡 Great location and even greater teammates!

So what are the next steps?

Our team is eager to learn about you! Send us your resume or LinkedIn profile below and we’ll explore working together!

Are you looking for an opportunity to jump-start your career in a thriving tech industry? Join us at Blend grow our business and execute our mission to help organizations leverage data and technology to make better decisions. With over 10 years of experience in the field of big data, top US customers such as Mastercard, Tripadvisor, and Roku choose us to develop innovative products.

We are seeking a Python Data Engineer to contribute to our next level of growth and expansion.

What is this position about?

This role is part of a Market Data initiative focused on building robust, scalable data and API-driven systems that support modern analytics, ML-driven workflows, and agentic solutions. The Python Data Engineer will work closely with cross-functional teams to design, implement, and maintain data pipelines and services that power market-data products.

This position requires strong Python expertise, solid data engineering fundamentals, and the ability to collaborate effectively with distributed teams working primarily in the Eastern Time (EST) zone.