Python Data Engineer chez Shyftlabs

POSITION OVERVIEWWe are seeking a highly skilled Python Data Engineer with a strong background in designing, developing, and maintaining scalable data solutions. The ideal candidate will have 5+ years of professional experience in Python and SQL, with proven expertise in building ETL/ELT pipelines, managing data streaming solutions. This role requires a hands-on engineer who can translate business requirements into reliable data systems, optimize performance, and ensure high data quality. ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses in various industries, by focusing on creating value through innovation.

Job Responsibilities

Develop and maintain data pipelines and ETL/ELT processes using Python

Design and implement scalable, high-performance applications

Work collaboratively with cross-functional teams to define requirements and deliver solutions

Develop and manage near real-time data streaming solutions using PubSub or Beam.

Contribute to code reviews, architecture discussions, and continuous improvement initiatives

Monitor and troubleshoot production systems to ensure reliability and Performance.

Basic Qualification

5+ years of professional software development experience with Python and SQL

Strong understanding of software engineering best practices (testing, version control, CI/CD)

Experience building and optimizing ETL/ELT processes and data pipelines

Proficiency with SQL and database concepts

Experience with data processing frameworks (e.g., Pandas)

Understanding of software design patterns and architectural principles

Ability to write clean, well-documented, and maintainable code

Experience with unit testing and test automation

Experience working with any cloud provider (GCP is preferred)

Experience with CI/CD pipelines and Infrastructure as code

Experience with Containerization technologies like Docker or Kubernetes

Preferred Qualification

Experience with GCP services, particularly Cloud Run and Dataflow

Experience with stream processing technologies (Pub/Sub)

Familiarity with big data technologies (Airflow)

Experience with data visualization tools and libraries

Knowledge of CI/CD pipelines with Gitlab and infrastructure as code with Terraform

Familiarity with platforms like Snowflake, Bigquery or Databricks,

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