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Description and Location Strong/expert Spark (PySpark) Using Jupyter Notebooks, Colab or DataBricks (preferred) Hands-on data pipeline development, ingest patterns in Azure Orchestration tools, ADF or Airflow SQL Denormalized Data modeling for big data systems Responsibilities and essential job functions include but are not limited to the following: Demonstrate deep knowledge of the data engineering domain to build and support non-interactive (batch, distributed) & real-time, highly available data, data pipeline, and technology capabilities Build fault-tolerant, self-healing, adaptive, and highly accurate data computational pipelines Provide consultation and lead the implementation of complex programs Develop and maintain documentation relating to all assigned systems and projects Tune queries running over billions of rows of data running in a distributed query engine Perform root cause analysis to identify permanent resolutions to software or business process issues.
We are seeking an experienced Databricks Data Engineer to design, develop, and maintain scalable data pipelines and cloud-based data platforms. The ideal candidate will have strong expertise in Databricks, PySpark, Python, SQL, Delta Lake, and cloud technologies (Azure/AWS)*, with experience building enterprise-scale data solutions that support analytics, reporting, and machine learning workloads.

Key Responsibilities
- Design, develop,



and optimize scalable ETL/ELT pipelines using Databricks and PySpark.
- Build and maintain data ingestion frameworks for batch and real-time data processing.
- Develop data models and implement data transformation logic using SQL and Python.
- Leverage Delta Lake for data management, data quality, and performance optimization.
- Implement data orchestration workflows using tools such as Azure Data Factory, Airflow, or Databricks Workflows.
- Collaborate with data architects, analysts, data scientists, and business stakeholders to understand requirements and deliver solutions.
- Optimize Databricks jobs and Spark applications for performance, scalability, and cost efficiency.
- Implement data governance, security, and compliance best practices.
- Monitor and troubleshoot production data pipelines and provide support for critical issues.
- Participate in code reviews, documentation, and knowledge-sharing activities. Technical

Skills:
Solid/expert Spark (PySpark) Using Jupyter Notebooks, Colab or DataBricks (preferred) Hands-on data pipeline development, ingest patterns in Azure Orchestration tools, ADF or Airflow SQL Denormalized Data modeling for big data systemsJob DescriptionData engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets.

Job Description




- Grade SpecificThe involves leading and managing a team of data engineers, overseeing data engineering projects, ensuring technical excellence, and fostering collaboration with stakeholders. They play a critical role in driving the success of data engineering initiatives and ensuring the delivery of reliable and high quality data solutions to support the organizations data driven objectives.
The base compensation range for this role in the posted location is $83,951 to $135,000Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.
S. and Canada, available benefits are determined by local pol

📌 Senior Data Engineer (Calgary)
🏢 Capgemini
📍 Calgary