Data Engineer

As a Data Engineer, you will be responsible for building digital-first, data-driven customer experiences to simplify the organization while ensuring data security. Your role will involve designing and delivering innovative data solutions using pipelines, modeling, and ETL frameworks. You will play a key role in enabling commercial success through actionable insights and scalable, streaming data ingestion solutions. Additionally, you will drive transformation by advocating improvements to data structures, metrics, and platforms. Key Responsibilities: - Develop a comprehensive understanding of enterprise data structures, metrics, and dependencies. - Design and deliver transformation solutions, including complex data extractions and integrations. - Build cost-effective, strategic data solutions by optimizing data platform costs. - Source new data using appropriate tools and integrate it into end-to-end data solutions. - Translate complex business requirements into reusable data engineering solutions to drive customer value. - Participate in the data engineering community to support strategic initiatives and best practices. - Build scalable data architectures and transform data to make it usable for analysts and data scientists. - Automate data engineering pipelines to improve reliability and efficiency. - Lead planning and design of complex data products and provide technical guidance to peers. Required Experience & Capabilities: - Strong understanding of data usage, dependencies, and customer impact across teams. - Experience in extracting value and features from large-scale data sets. - Proven experience in ETL technical design, data quality testing, cleansing, and monitoring. - Hands-on experience with data sourcing, exploration, analysis, warehousing, and data modeling. - Proficiency in developing data solutions using Python or Java. - Strong understanding of data lake and data warehouse architectures. - Experience working with cloud platforms such as AWS, Azure, or GCP. - Proficiency in SQL, Hive, Parquet, and Delta Lake. - Experience using Git, version control, CI/CD pipelines, and Agile methodologies. As a Data Engineer, you will be responsible for building digital-first, data-driven customer experiences to simplify the organization while ensuring data security. Your role will involve designing and delivering innovative data solutions using pipelines, modeling, and ETL frameworks. You will play a key role in enabling commercial success through actionable insights and scalable, streaming data ingestion solutions. Additionally, you will drive transformation by advocating improvements to data structures, metrics, and platforms. Key Responsibilities: - Develop a comprehensive understanding of enterprise data structures, metrics, and dependencies. - Design and deliver transformation solutions, including complex data extractions and integrations. - Build cost-effective, strategic data solutions by optimizing data platform costs. - Source new data using appropriate tools and integrate it into end-to-end data solutions. - Translate complex business requirements into reusable data engineering solutions to drive customer value. - Participate in the data engineering community to support strategic initiatives and best practices. - Build scalable data architectures and transform data to make it usable for analysts and data scientists. - Automate data engineering pipelines to improve reliability and efficiency. - Lead planning and design of complex data products and provide technical guidance to peers. Required Experience & Capabilities: - Strong understanding of data usage, dependencies, and customer impact across teams. - Experience in extracting value and features from large-scale data sets. - Proven experience in ETL technical design, data quality testing, cleansing, and monitoring. - Hands-on experience with data sourcing, exploration, analysis, warehousing, and data modeling. - Proficiency in developing data solutions using Python or Java. - Strong understanding of data lake and data warehouse architectures. - Experience working with cloud platforms such as AWS, Azure, or GCP. - Proficiency in SQL, Hive, Parquet, and Delta Lake. - Experience using Git, version control, CI/CD pipelines, and Agile methodologies.