Data Engineer I

As a Data Engineer I with 10 to 12 years of experience, your role will involve designing, building, and optimizing data systems, pipelines, and workflows. You will need strong technical skills, analytical thinking, and collaboration abilities to ensure reliable, scalable, and high-performance data infrastructure. Your responsibilities will include: - Designing, developing, and maintaining scalable data pipelines and ETL/ELT processes. - Building and optimizing data models, data lakes, and data warehouse systems for analytics and product requirements. - Ensuring data quality, accuracy, consistency, and reliability across all data touchpoints. - Collaborating with Product, Engineering, and Analytics teams for data-driven decision-making. - Implementing performance optimization techniques for query processing, workflow execution, and data storage. - Identifying and resolving bottlenecks in data flow through architectural improvements and automation. - Developing data ingestion frameworks integrating structured, semi-structured, and unstructured datasets. - Managing end-to-end data lifecycle including ingestion, transformation, storage, governance, and security. - Utilizing monitoring tools to track pipeline health, resolve issues, and minimize downtime. - Contributing to best practices in data engineering, coding standards, version control, and documentation. - Supporting organizational change initiatives for data modernization and platform upgrades. - Ensuring alignment of data infrastructure with business goals, compliance standards, and operational KPIs. Required Skills & Competencies: - Proficiency in SQL, data modeling, and relational and NoSQL databases. - Hands-on experience with modern ETL/ELT tools and pipeline orchestration frameworks. - Expertise in Python, Scala, or Java for data engineering tasks. - Familiarity with cloud platforms like AWS, Azure, or GCP. - Experience with big data technologies such as Spark, Hadoop, Kafka, or Databricks. - Understanding of data warehousing concepts and distributed processing. - Ability to diagnose performance issues, optimize pipelines, and improve processing workflows. - Proficiency in data visualization and analytics tools for insight generation. - Excellent communication and collaboration skills with cross-functional teams. - Data-driven mindset to interpret operational KPIs and drive measurable improvements. - Bachelor's degree in Computer Science, Engineering, Information Systems, or related field. As a Data Engineer I with 10 to 12 years of experience, your role will involve designing, building, and optimizing data systems, pipelines, and workflows. You will need strong technical skills, analytical thinking, and collaboration abilities to ensure reliable, scalable, and high-performance data infrastructure. Your responsibilities will include: - Designing, developing, and maintaining scalable data pipelines and ETL/ELT processes. - Building and optimizing data models, data lakes, and data warehouse systems for analytics and product requirements. - Ensuring data quality, accuracy, consistency, and reliability across all data touchpoints. - Collaborating with Product, Engineering, and Analytics teams for data-driven decision-making. - Implementing performance optimization techniques for query processing, workflow execution, and data storage. - Identifying and resolving bottlenecks in data flow through architectural improvements and automation. - Developing data ingestion frameworks integrating structured, semi-structured, and unstructured datasets. - Managing end-to-end data lifecycle including ingestion, transformation, storage, governance, and security. - Utilizing monitoring tools to track pipeline health, resolve issues, and minimize downtime. - Contributing to best practices in data engineering, coding standards, version control, and documentation. - Supporting organizational change initiatives for data modernization and platform upgrades. - Ensuring alignment of data infrastructure with business goals, compliance standards, and operational KPIs. Required Skills & Competencies: - Proficiency in SQL, data modeling, and relational and NoSQL databases. - Hands-on experience with modern ETL/ELT tools and pipeline orchestration frameworks. - Expertise in Python, Scala, or Java for data engineering tasks. - Familiarity with cloud platforms like AWS, Azure, or GCP. - Experience with big data technologies such as Spark, Hadoop, Kafka, or Databricks. - Understanding of data warehousing concepts and distributed processing. - Ability to diagnose performance issues, optimize pipelines, and improve processing workflows. - Proficiency in data visualization and analytics tools for insight generation. - Excellent communication and collaboration skills with cross-functional teams. - Data-driven mindset to interpret operational KPIs and drive measurable improvements. - Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.