The data engineering and integration lead will be measured on their ability to plan and execute the integration of data across transactional systems and to data analytics and warehousing systems, to streamline project executions and facilitate the analysis of data in new ways to deliver business insights and efficiencies.
This role will require both creative and collaborative work with IT and business areas. It will involve promoting effective data management practices, sound design and reusability, and a better understanding of how these are essential for data analytics.
Under the guidance of the Director and their designee, they will be tasked with working with key business stakeholders, IT experts and subject-matter experts to plan and deliver optimal solutions across systems. Additionally, they will be expected to collaborate with data analysts and data consumers, and work on models and procedures to optimize them for data quality, security, and performance optimization of pipelines across various environments, and put them into production leading to potentially large productivity gains.
- Required 1 Years Bachelor’s degree in computer science, statistics, applied mathematics, data management, information systems, information science or a related field.
- Desired 1 Years Advanced degree (MS) in computer science, statistics, applied mathematics, information science (MIS), data management, information systems.
- Required 4 Years Possess combination of data integration and engineering expertise, IT skills, data governance skills, and analytics skills.
- Required 6 Years Experience in data architecture and integration design, and data management disciplines, data warehousing, Big Data related initiatives.
- Required 3 Years Experience leading cross-functional teams and collaborating with business and technical stakeholders to initiate, plan, and execute.
- Required 6 Years Strong experience documenting complex requirements, considering ambiguous information and engaging cross functionally, to propose elegant designs.
- Required 4 Years Strong experience with various Data Management architectures like Data Warehouse, Data Lake, Data Hub, Operational Data Stores.
- Required 3 Years Strong ability to design, build and manage data pipelines for data structures.
- Required 4 Years Strong experience in working with and optimizing existing ETL processes and data integration and data preparation flow.
- Required 6 Years Strong experience in working with large, heterogeneous datasets.
- Required 3 Years Experience working with data governance/data quality and data security teams and specifically information stewards.
- Required 4 Years Demonstrated success in working with large, heterogeneous datasets to extract business value using popular data preparation tools.
- Required 6 Years Strong experience with popular database programming languages including SQL, PL/SQL, others for relational databases.
- Required 3 Years Strong experience in working with SQL on Hadoop query languages and tools including HIVE, Impala, Presto, and others.
- Required 4 Years Knowledge of and experience with multiple data integration platforms.
- Required 6 Years Strong experience with advanced analytics tools for Object-oriented/object function scripting.
- Required 6 Years Strong experience in working with both open-source and commercial message queuing technologies.
- Required 6 Years Knowledge about various architectures, patterns and protocols.