Data Engineer

About the role The Data Engineer – Lakehouse & Data Products is responsible for building and maintaining scalable data solutions and data products using a modern Lakehouse architecture deployed on AWS and Google Cloud Platform (GCP). This role is hands‑on and delivery‑focused. You will work under the guidance of senior engineers and architects to implement reliable data pipelines, curated datasets, and domain‑aligned data products that support analytics, reporting, and downstream AI/ML use cases.

Key Responsibilities 1. Lakehouse Data Engineering (AWS & GCP) Build and maintain Lakehouse‑based data pipelines using object storage (Amazon S3, Google Cloud Storage) and open table formats (e.g., Apache Iceberg). Develop batch and streaming pipelines using: AWS services such as AWS Glue, Apache Spark, Kinesis, and Athena GCP services such as Dataproc, Dataflow, Pub/Sub, and BigQuery Implement medallion architecture patterns (raw / bronze → silver → gold) for structured data processing. 2.

Data Product Development Implement curated and consumption‑ready datasets as part of domain‑oriented data products. Work with Data Product Owners and senior engineers to understand requirements and translate them into pipelines and data models. Ensure data products are consistent, reusable, and aligned with enterprise standards. 3.

Data Modeling & Quality Support development of analytical data models optimized for BI and reporting use cases. Implement data quality checks and validations within pipelines. Assist with schema management and controlled schema evolution. 4.

DataOps & Automation Contribute to CI/CD pipelines for data pipeline deployments. Follow established DataOps and DevOps practices to improve reliability and deployment speed. Monitor pipelines and address data failures or performance issues with guidance from senior team members. 5.

Collaboration & Continuous Improvement Collaborate with data engineers, platform teams, and DevOps to deliver end‑to‑end data solutions. Participate in code reviews and design discussions. Continuously improve pipeline performance, reliability, and maintainability.

Required Qualifications 2–4 years of experience in data engineering or related roles. Hands‑on experience building data pipelines on cloud platforms. Experience with AWS data services (e.g., S3, Glue, Kinesis, Athena).

Experience with GCP data services (e.g., GCS, Dataproc, Dataflow, BigQuery). Familiarity with Lakehouse concepts and open table formats such as Apache Iceberg. Proficiency in Python and SQL.

Understanding of batch and streaming data processing concepts. Preferred Qualifications Experience working in multi‑cloud data environments. Familiarity with orchestration tools (e.g., Airflow or managed equivalents).

Exposure to CI/CD, Infrastructure as Code, or cloud automation. Experience supporting analytics or AI/ML workloads. Prior experience working in a data product‑oriented team.

Benefits We are committed to offering competitive benefits programs for all of our employees, and enhancing our programs when necessary. Enjoy your best years with our retirement savings plan Have peace of mind and body with our health insurance Make yourself a priority with flexible schedules, parental leave and our holiday purchase scheme Drive forward your career through professional development opportunities Achieve your personal goals with our Employee Assistance Programme. Our commitment to you Our greatest assets are the expertise, creativity and passion of our employees.

We strive to provide a great place to work that attracts, develops and retains the best talent, promotes employee engagement, fosters teamwork and ultimately drives innovation for the benefit of our customers. We strive to create an environment where you feel that you belong, with diversity and inclusion as the engine to growth and innovation. We develop and deploy best-in-class programs and practices, providing enriching career opportunities, listening to employee feedback and always challenging ourselves to do better.

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