Data Engineer

7 days ago

Canada Summer Full time

Title: Data Engineer

Location: Remote Canada

About this Role:

As a Data Engineer, you will play a crucial role in designing, building, and optimizing our data infrastructure. You'll be responsible for developing scalable data pipelines, implementing ETL processes, and ensuring the quality and integrity of our data. Your expertise will contribute to the success of our data-driven initiatives, supporting data scientists, software developers, and business stakeholders. If you are passionate about working with large datasets, implementing efficient data solutions, and staying at the forefront of data engineering technologies, we invite you to join our dynamic team.

Responsibilities:

Data Pipeline Development:

  • Design, build, and maintain scalable and efficient data pipelines for the acquisition, transformation, and loading of large volumes of data from various sources.
  • Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and ensure that data pipelines meet business needs.

Data Modeling:

  • Develop and implement data models, schema designs, and database structures to support the organization's data needs.
  • Optimize database performance and ensure data integrity and consistency.

ETL Processes:

  • Create Extract, Transform, Load (ETL) processes to clean, transform, and aggregate raw data into a format suitable for analysis.
  • Implement and maintain data integration solutions between different systems and platforms.

Data Warehousing:

  • Design and maintain data warehouse systems to store and organize large volumes of structured and unstructured data.
  • Ensure the scalability and efficiency of data warehousing solutions.

Data Quality and Governance:

  • Implement data quality checks, validation rules, and governance processes to ensure the accuracy and reliability of data.
  • Work on data profiling and data cleansing activities.

Big Data Technologies:

  • Utilize big data technologies such as Hadoop, Spark, and related frameworks for processing and analyzing large datasets.
  • Stay updated with emerging technologies in the big data ecosystem.

Collaboration:

  • Collaborate with cross-functional teams, including data scientists, analysts, software developers, and business stakeholders, to understand data needs and deliver effective solutions.

Monitoring and Optimization:

  • Implement monitoring and logging mechanisms to track the performance and health of data pipelines, ML models and business dashboards.
  • Optimize and tune existing data infrastructure for improved efficiency and performance.

Security and Compliance:

  • Implement security measures to protect sensitive data and ensure compliance with data privacy regulations.
  • Collaborate with the security team to establish and enforce data security policies.

Documentation:

  • Document data engineering processes, data flows, and system architecture to ensure knowledge transfer and maintainability.
  • Provide training and support to other team members on data engineering best practices.

Continuous Learning:

  • Stay informed about industry trends, best practices, and emerging technologies in data engineering.
  • Participate in training and development activities to enhance skills and knowledge.

Responsibilities (cont.)

  • Design, automate, optimize and scale end-to-end workflows for the acquisition and transformation of data.
  • Implement and optimize ETL processes to ensure the accuracy and reliability of our data.
  • Build and maintain data models and structures to support analytics and reporting.
  • Help productionize ML models and data artifacts.
  • Collaborate with cross-functional teams to understand data requirements and deliver effective solutions.
  • Utilize big data technologies for processing and analyzing large datasets.
  • Monitor and optimize data infrastructure for performance and efficiency.
  • Implement security measures and ensure compliance with data privacy regulations.
  • Document data engineering processes, flows, and system architecture.
  • Stay informed about industry trends and emerging technologies in data engineering.

Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • Proven experience as a Data Engineer or in a similar role.
  • Proficiency in programming languages such as Python, Java, or Scala.
  • Strong knowledge of SQL and experience with relational and NoSQL databases.
  • Experience with big data processing frameworks (e.g., Hadoop, Spark).
  • Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data services.
  • Expertise in ETL tools and processes.
  • Understanding of data modeling concepts and techniques.
  • Strong problem-solving and analytical skills.
  • Excellent communication and collaboration abilities.
  • Experience with version control systems (e.g., Git) and CI/CD processes is a plus.
  • Familiarity with containerization tools (e.g., Docker, Kubernetes)

You'll love working at Summer because of our...

  • Amazing purpose-driven team and culture
  • Competitive salary and stock options.
  • Unlimited, flexible PTO for exempt employees
  • Excellent medical, dental and vision coverage
  • Paid maternity and paternity leave

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