Data Engineer - Fleet Analytics & Data Infrastructure

Vikas Logistics Ltd.; United Kingdom; Remote; GBP 65,000 - 90,000; Full time

Benefits offered by this job

Pension scheme with employer contrib

Learning and development budget

Latest tech equipment provided

25 days annual leave plus bank hols

Job summary

Vikas Logistics Ltd. is seeking a skilled Data Engineer to design and build robust data infrastructure for fleet analytics.

You will develop ETL pipelines and data warehousing solutions to transform how logistics data is used, enabling advanced analytics across teams. Ideal candidates have a strong background in Python, SQL, and cloud-based data platforms, with hands-on experience in ETL tooling and data quality practices.

Qualifications

• Degree in Computer Science, Engineering, or related field.
• 3+ years experience with big data technologies.
• Proficiency in Python and SQL.
• Experience with cloud platforms (AWS, GCP, or Azure).
• Knowledge of data warehousing tools (Snowflake, BigQuery, Redshift).
• Experience with ETL tools (Airflow, dbt, or similar).

Responsibilities

• Design, build, and maintain scalable data pipelines.
• Develop ETL processes for fleet telemetry and logistics data.
• Build and optimize data warehousing solutions.
• Collaborate with data scientists to enable advanced analytics.
• Implement data quality monitoring and validation.
• Optimize database performance and query efficiency.
• Document data architecture and maintain technical specifications.

Skills

Python

SQL

ETL Tools

Git

CI/CD

Big Data

Education

Bachelor's degree in Computer Science or related field

Tools

Snowflake

BigQuery

Redshift

Airflow

dbt

Job description

Vikas Logistics Ltd. is seeking a skilled Data Engineer to design and build robust data infrastructure for fleet analytics.

You will develop ETL pipelines and data warehousing solutions to transform how logistics data is used, enabling advanced analytics across teams. Ideal candidates have a strong background in Python, SQL, and cloud-based data platforms, with hands-on experience in ETL tooling and data quality practices.