Senior Data Engineer

5 days ago


Canada Capgemini Engineering Full time
About the Role

We are seeking a highly skilled Senior Data Engineer to join our team at Capgemini Engineering. As a Senior Data Engineer, you will play a key role in designing and implementing distributed data processing solutions and highly loaded database solutions for various business cases.

Key Responsibilities
  • Investigate and build solutions for existing technical challenges.
  • Provide instruction, direction, and leadership to a development team to achieve project goals.
  • Prepare functional and design specifications, and approve them with partners.
  • Ensure assigned areas are delivered within required quality objectives.
  • Provide estimations, agree task duration with the manager, and give to project plan of assigned areas.
  • Analyze scope of alternative solutions and make decisions based on technical expertise.
  • Lead functional and architectural design of assigned areas, ensuring design decisions meet design requirements.
  • Address area-level risks, provide, and implement mitigation plans.
  • Report on area readiness/quality and raise red flags in crisis situations.
  • Responsible for resolving crisis situations within their area of responsibility.
  • Initiate and conduct code reviews, code standards, conventions, and guidelines.
  • Suggest technical and functional improvements to make valuable contributions to the product.
  • Constantly improve their professional level.
  • Collaborate with other teams.
Requirements
  • 5+ years of professional experience.
  • University degree or equivalent experience in Computer Related Sciences or similar.
  • Proficiency in writing and optimizing SQL queries that will run against Snowflake or Delta tables.
  • Proficiency in Python programming languages.
  • Validated experience in ETL orchestration and workflow management tool Airflow.
  • Experience in Spark, Snowflake & Databricks.
  • Experience in Flink & Tirno implementation.
  • Knowledge in Spark streaming and Spark job optimizations and configuring the cluster for a Spark job depending on the load.
  • Good knowledge of Kafka and integrating Kafka with Pyspark applications.
  • Knowledge of Databricks and scheduling jobs using Workflow.
  • Excellent interpersonal skills and experience working with technical and non-technical teams.
  • Experience in AWS (EC2/S2/IAM).
About Capgemini Engineering

Capgemini Engineering is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society.

We are a responsible and diverse group of 340,000 team members in more than 50 countries, with a strong over 55-year heritage. We are trusted by our clients to unlock the value of technology to address the entire breadth of their business needs.

We deliver end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by our market-leading capabilities in AI, cloud, and data, combined with our deep industry expertise and partner ecosystem.

We reported 2023 global revenues of €22.5 billion.

We are committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.



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