Lead Data Engineer - ETL/Power BI

Description : About the Role : We are seeking a talented Lead Data Engineer to join our team and play a pivotal role in transforming raw data into valuable insights. As a Data Engineer, you will design, develop, and maintain robust data pipelines and infrastructure to support our organization's analytics and decision-making processes. Responsibilities : - Data Pipeline Development : Build and maintain scalable data pipelines to extract, transform, and load (ETL) data from various sources (e.g., databases, APIs, files) into data warehouses or data lakes. - Data Infrastructure : Design, implement, and manage data infrastructure components, including data warehouses, data lakes, and data marts. - Data Quality : Ensure data quality by implementing data validation, cleansing, and standardization processes. - Team Management : Able to handle team. - Performance Optimization : Optimize data pipelines and infrastructure for performance and efficiency. - Collaboration : Collaborate with data analysts, scientists, and business stakeholders to understand their data needs and translate them into technical requirements. - Tool and Technology Selection : Evaluate and select appropriate data engineering tools and technologies (e.g., SQL, Python, Spark, Hadoop, cloud platforms). - Documentation : Create and maintain clear and comprehensive documentation for data pipelines, infrastructure, and processes. Skills : - Strong proficiency in SQL and at least one programming language (e.g., Python, Java). - Experience with data warehousing and data lake technologies (e.g., Snowflake, AWS Redshift, Databricks). - Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and cloud-based data services. - Understanding of data modeling and data architecture concepts. - Experience with ETL/ELT tools and frameworks. - Excellent problem-solving and analytical skills. - Ability to work independently and as part of a team. Preferred Qualifications : - Experience with real-time data processing and streaming technologies (e.g., Kafka, Flink). - Knowledge of machine learning and artificial intelligence concepts. - Experience with data visualization tools (e.g., Tableau, Power BI). - Certification in cloud platforms or data engineering. Description : About the Role : We are seeking a talented Lead Data Engineer to join our team and play a pivotal role in transforming raw data into valuable insights. As a Data Engineer, you will design, develop, and maintain robust data pipelines and infrastructure to support our organization's analytics and decision-making processes. Responsibilities : - Data Pipeline Development : Build and maintain scalable data pipelines to extract, transform, and load (ETL) data from various sources (e.g., databases, APIs, files) into data warehouses or data lakes. - Data Infrastructure : Design, implement, and manage data infrastructure components, including data warehouses, data lakes, and data marts. - Data Quality : Ensure data quality by implementing data validation, cleansing, and standardization processes. - Team Management : Able to handle team. - Performance Optimization : Optimize data pipelines and infrastructure for performance and efficiency. - Collaboration : Collaborate with data analysts, scientists, and business stakeholders to understand their data needs and translate them into technical requirements. - Tool and Technology Selection : Evaluate and select appropriate data engineering tools and technologies (e.g., SQL, Python, Spark, Hadoop, cloud platforms). - Documentation : Create and maintain clear and comprehensive documentation for data pipelines, infrastructure, and processes. Skills : - Strong proficiency in SQL and at least one programming language (e.g., Python, Java). - Experience with data warehousing and data lake technologies (e.g., Snowflake, AWS Redshift, Databricks). - Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and cloud-based data services. - Understanding of data modeling and data architecture concepts. - Experience with ETL/ELT tools and frameworks. - Excellent problem-solving and analytical skills. - Ability to work independently and as part of a team. Preferred Qualifications : - Experience with real-time data processing and streaming technologies (e.g., Kafka, Flink). - Knowledge of machine learning and artificial intelligence concepts. - Experience with data visualization tools (e.g., Tableau, Power BI). - Certification in cloud platforms or data engineering.