Python Data Developer with Time Series

Python Data Developer with Time Series

Posted 4 days ago by ST Global Tech LLC

Negotiable
Undetermined
Hybrid
Leeds, England, United Kingdom

Summary: The role of Software Engineer focuses on Python development with a specialization in time series data analysis. The position requires extensive experience in programming and data manipulation, along with strong communication skills. The candidate will work in a hybrid environment, splitting time between the client office and remote work. The role is expected to last a minimum of one year.

Key Responsibilities:

  • Develop and maintain Python applications with a focus on time series data.
  • Utilize data manipulation and analysis libraries such as Pandas and NumPy.
  • Implement software engineering best practices including version control and unit testing.
  • Create interactive dashboards using Plotly Dash and integrate REST APIs.

Key Skills:

  • 12+ years of experience in software engineering.
  • Proficient in Python programming and object-oriented programming.
  • Experience with data manipulation and analysis using Pandas and NumPy.
  • Strong understanding of software engineering best practices.
  • Experience with Plotly Dash for dashboard creation.
  • Strong written and verbal communication skills.

Salary (Rate): undetermined

City: Leeds

Country: United Kingdom

Working Arrangements: hybrid

IR35 Status: undetermined

Seniority Level: Senior

Industry: IT

Detailed Description From Employer:

Software Engineer

Location: Leeds, UK

Hybrid – 3 days at client office and 2 days remote

Duration: Minimum 1 yr.

Required Skills- 12 + years’ experience must

Senior - Python Development - Time Series/ + JD

Relevant experience on timeseries/data package

Education: Software engineer

Soft Skills: Strong written and verbal communication skills

Experience: Hands on programming experience with:

  • i. Proficient Python Programming
  • ii. Key skills: Functions, classes, and object-oriented programming, List comprehensions, generators, Error handling,
  • iii. Working with virtual environments and package management (pip, venv)

Data Manipulation & Analysis (Pandas & NumPy)

  • i. Key libraries: pandas, numpy, (optional: polars)
  • ii. Key skills: Data cleaning and preprocessing, Handling missing values, grouping, merging, pivoting, aggregations, and SQL

Software Engineering Best Practices

  • i. Key practices: Version control with Git. Writing modular, reusable code. Unit testing (e.g., with pytest). Code documentation and docstrings. Using linters and formatters

Plotly Dash

  • i. Key skills: Customizing with Plotly Graph Objects for advanced interactivity.
  • ii. Creating dashboards with Dash: Callbacks, Layouts (HTML & CSS integration), Components (Dropdowns, sliders, graphs, tables).
  • iii. REST APIs: Fetching or sending data to backend services