Description

About the Role

We are looking for a Senior Data Engineer to be embedded with one of our primary clients for a long term, full-time engagement. You’ll be responsible for designing and maintaining scalable data pipelines, enabling analytics, and contributing to a robust data platform that supports BI and AI workloads. You may also be expected to collaborate in academic partnerships and with industry leaders to drive innovation and knowledge exchange.

Responsibilities

  • Design, develop, and optimize scalable data pipelines using PySpark and related distributed frameworks.
  • Build and maintain high-quality ETL/ELT pipelines across diverse data sources using AWS services.
  • Model and transform data for analytics use cases across data lakes, warehouses, and semantic layers.
  • Implement robust data validation and quality processes to ensure data integrity.
  • Support BI and analytics workflows, including metric definitions, modelling, and dashboard development.
  • Collaborate in an agile environment with data architects, analysts, scientists, product owners, and scrum teams to deliver end-to-end data & AI products.
  • Work directly with clients to deliver complete data solutions, insights, and reports.
  • Participate in academic and industry collaborations to align data strategies with emerging trends.

Required Skills & Experience

  • Strong proficiency in SQL, data analysis, and PySpark (or equivalent distributed processing frameworks).
  • Deep understanding of ETL/ELT, data lakes, data warehousing, and orchestration workflows.
  • Hands-on experience with AWS data and analytics services (e.g., S3, Glue, Lambda, Step Functions).
  • Advanced SQL skills for building efficient, scalable queries over large datasets.
  • Ability to translate business requirements into reliable technical solutions with a focus on data quality.
  • Strong interest in analytics and BI; this role includes substantial analytics engineering work.
  • Excellent communication and teamwork skills.

Preferred Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related fields.
  • 5+ years of professional experience in data engineering with strong analytical foundations.
  • Experience with at least one BI tool (e.g., Metabase, Looker Studio, PowerBI, Tableau).
  • Familiarity with retail/fashion/wholesale domains, ERP systems (SAP ECC/S4HANA, CDS Views), and supply-chain processes.
  • Experience with cloud-native data platforms (BigQuery, Snowflake, Redshift).
  • Familiarity with dbt and semantic-layer modelling.
  • Experience working in agile product teams and collaborating on academic or industry projects.