Engineering · Full-time · Colombia
Senior Python Backend Engineer - LATAM
This position offers you the opportunity to join a fast-growing technology organization that is redefining productivity paradigms in the software engineering industry. Thanks to our flexible, distributed model of global operation and the high caliber of our experts, we have enjoyed triple digit growth over the past five years, creating amazing career opportunities for our people.
If you want to accelerate your career working with like-minded subject matter experts, solving interesting problems and building the products of tomorrow, this opportunity is for you.
The Impact You'll Make:
Develop data infrastructure to support the next generation of banking products and data initiatives.
Build, opertaionalize and optimize data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams.
Support other software developers, database architects, data analysts and data scientists on data initiatives and ensure optimal data delivery architecture is consistent throughout ongoing projects.
Work with engineers across the company to build new features at a large scale.
Improve engineering standards, tooling, and processes.
Technology Stack:
Python
AWS
Pandas / Numpy / Boto/ S3FS / Flask
Fast API / Pyarrow / Pyspark
SQL
What You'll Bring To Us:
+7 years of experience using Python on Cloud platforms like AWS.
Proficient in programming in Python and experience with packages like Pandas, Numpy, Boto, S3FS, Flask, FastAPI, Pyarrorw, Pyspark etc.
Knowledge of at least one Python web framework (FastAPI, Flask, Django, Bottle, Tornado, Dash, etc).
Expert in SQL programming and experience working with relational databases, as well as working familiarity with a variety of databases (Postgres/Redshift/MySQL).
Excellent written and verbal English communication skills.
Assemble large, complex data sets that meet functional / non-functional business requirements.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability,
Operationalizing, Improving the quality and reliability of data pipelines (monitoring, retry, failure detection)
Data Platform and Self-serving Data Infrastructure.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using various data tools and cloud services.
Design and build abstractions that hide the complexity of the underlying big data processing and execution stack and that allow data consumers/partners to focus on their strengths: product, data modeling, data analysis, search, information retrieval, and machine learning.
Build processes and infrastructure to manage lifecycle of datasets: data structures, metadata, dependency and workload management.
Building internal services and tools to help in-house partners implement, deploy and analyze datasets with a high level of autonomy and limited friction.
Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
Working experience in data analytics (data wrangling, integration, visualization), and reporting using BI (Business Intelligence) tools
Some of the benefits you’ll enjoy working with us:
Come and join our #ParserCommunity.
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