Job description

Description: As a Data Engineer, you'll be responsible for designing, building, and maintaining data pipelines and infrastructure to support data analytics, machine learning, and business intelligence initiatives.

Responsibilities

  • Designing and developing scalable, reliable, and efficient data processing systems and architectures to ingest, transform, and store large volumes of structured and unstructured data.
  • Building and optimizing data pipelines and ETL (Extract, Transform, Load) processes to ensure data quality, integrity, and accessibility for analysis and reporting.
  • Collaborating with data scientists, analysts, and business stakeholders to understand data requirements and translate them into technical solutions and infrastructure designs.
  • Implementing data governance, security, and compliance measures to protect sensitive information and ensure regulatory compliance.
  • Monitoring and optimizing data infrastructure performance, reliability, and cost efficiency through automation, monitoring tools, and infrastructure as code (IaC) practices.

Qualifications

  • Strong programming skills in languages such as Python, Java, or Scala, with experience in data processing frameworks and technologies such as Apache Spark, Apache Kafka, or Hadoop.
  • Proficiency in SQL and database technologies such as PostgreSQL, MySQL, or NoSQL databases.
  • Knowledge of cloud platforms and services such as AWS, Azure, or Google Cloud Platform, and experience with cloud-based data services such as Amazon Redshift, Google BigQuery, or Azure SQL Database.
  • Familiarity with data modeling, schema design, and data warehousing concepts.
  • Previous experience in data engineering, software engineering, or related roles.

Benefits

  • Competitive salary and opportunities for career growth in the field of data engineering and analytics.
  • Exposure to cutting-edge technologies and projects that leverage data to drive business insights and innovation.
  • Collaboration with cross-functional teams of data scientists, analysts, and business stakeholders to deliver data-driven solutions.
  • Professional development opportunities to enhance skills and knowledge in data engineering, cloud computing, and analytics.
  • Contribution to the development of scalable and robust data infrastructure that supports business intelligence and decision-making processes.

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