Data Engineering & Big Data – Spark / Databricks / ETL Engineer

We are a $13+ billion global technology company, home to more than 224,000 people across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud, and AI, powered by a broad portfolio of technology services and products.HCLTech is a globally recognized leader in the Tech and IT industry, but we’ve never forgotten the startup mindset that got us here. We’ve always approached our work with an idea-first attitude because every one of our accomplishments —no matter how big or small —can be traced back to an idea’s single spark.

It’s that spark —that inner drive —that sets our people apart from our competitors. It enables us not just to pull off game-changing feat after game-changing feat but to better our world in the process. We want you to find your spark. Because that’s what drives you to be better, be more and ultimately, be more fulfilled.

Overview

The Data Engineering & Big Data Engineer provides technical expertise in the design, development and maintenance of data pipelines and big data platforms. The role focuses on data ingestion, transformation, quality, monitoring and delivery of reliable datasets for enterprise analytics, reporting and downstream applications.

Responsibilities

• Design, develop and maintain scalable data pipelines and data integration workflows.
• Implement ETL / ELT processes using Spark, PySpark, Databricks or equivalent technologies.
• Work with structured and semi-structured data from multiple enterprise sources.
• Support data quality controls, monitoring, troubleshooting and performance optimization.
• Contribute to data modeling, data transformation and dataset documentation.
• Collaborate with business, data, architecture, application and production teams.
• Support production incidents, technical investigations and continuous improvement actions.
• Document data flows, technical procedures and operational standards.

Mandatory skills

• Strong experience in data engineering or big data development.
• Hands‑on experience with Spark, PySpark, Databricks or equivalent big data technologies.
• Strong SQL skills and good knowledge of data transformation principles.
• Experience designing and maintaining ETL / ELT pipelines.
• Good knowledge of Python for data processing or automation.
• Understanding of data quality, monitoring and operational support activities.
• Ability to troubleshoot data pipeline issues and optimize performance.
• Strong communication skills in English.

Specific requirements

• Ability to work autonomously in a complex enterprise data environment.
• Strong analytical mindset and attention to data quality.
• Ability to document data flows, technical choices and operational procedures.
• Availability for hybrid work in Paris.

Appreciated skills

• Data Lake or Data Warehouse experience.
• Orchestration tools such as Airflow or equivalent.