Data Engineer

As a Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines and architectures. You will work closely with data scientists, analysts, and software engineers to ensure the availability, integrity, and quality of data for analytical and operational needs. - Design, develop, and maintain robust ETL pipelines to collect, process, and store data from multiple sources - Build and optimize data models for analytics, reporting, and operational needs - Implement best practices for data governance, data quality, and data security - Collaborate with stakeholders to understand data requirements and translate them into technical solutions - Integrate new data sources and expand the data platform capabilities - Monitor and troubleshoot data workflows and infrastructure issues - Maintain documentation related to data architecture, data sources, and data flows Minimum Requirements : - Bachelors or Masters degree in Computer Science, Engineering, Information Technology, or related field - 3-6 years of proven experience working as a Data Engineer. - Strong proficiency in SQL, Python, or Scala - Experience with big data technologies, such as Hadoop, Spark, Kafka, etc. - Familiarity with cloud platforms (AWS, GCP, Azure) and cloud-native data solutions - Experience with data warehousing (e.g., Redshift, Snowflake, BigQuery) - Good understanding of ETL concepts, data modeling, and data architecture - Experience with workflow orchestration tools (e.g., Airflow, Luigi) - Excellent problem-solving skills and attention to detail - Strong communication and collaboration skills Preferred Requirements : - Experience in real-time data processing and streaming - Knowledge of machine learning workflows and MLOps - Exposure to DevOps practices and CI/CD pipelines for data projects As a Data Engineer, you will be responsible for designing, building, and maintaining scalable data pipelines and architectures. You will work closely with data scientists, analysts, and software engineers to ensure the availability, integrity, and quality of data for analytical and operational needs. - Design, develop, and maintain robust ETL pipelines to collect, process, and store data from multiple sources - Build and optimize data models for analytics, reporting, and operational needs - Implement best practices for data governance, data quality, and data security - Collaborate with stakeholders to understand data requirements and translate them into technical solutions - Integrate new data sources and expand the data platform capabilities - Monitor and troubleshoot data workflows and infrastructure issues - Maintain documentation related to data architecture, data sources, and data flows Minimum Requirements : - Bachelors or Masters degree in Computer Science, Engineering, Information Technology, or related field - 3-6 years of proven experience working as a Data Engineer. - Strong proficiency in SQL, Python, or Scala - Experience with big data technologies, such as Hadoop, Spark, Kafka, etc. - Familiarity with cloud platforms (AWS, GCP, Azure) and cloud-native data solutions - Experience with data warehousing (e.g., Redshift, Snowflake, BigQuery) - Good understanding of ETL concepts, data modeling, and data architecture - Experience with workflow orchestration tools (e.g., Airflow, Luigi) - Excellent problem-solving skills and attention to detail - Strong communication and collaboration skills Preferred Requirements : - Experience in real-time data processing and streaming - Knowledge of machine learning workflows and MLOps - Exposure to DevOps practices and CI/CD pipelines for data projects