AArete is looking for a Data Engineering Lead to join our growing team and support our clients’ needs for data driven analytics.
Guided by AArete’s shared values, we work in an environment where collaboration, teamwork, respect, and openness are highly valued.
This team is at the forefront of innovation and development within the company, driving the creation of a novel and scalable product that can benefit our clients.
The ideal candidate will have a solid understanding of data architecture technologies, high throughput data processing, and big data platforms.
High level responsibilities will include designing, creating, deploying and managing data architectures, storage, integration, and consumption of enterprise data managed by different data entities and IT systems, as well as any applications using or processing that data.
Why AArete?
AArete’s mission is to increase client profitability while improving the capabilities of our clients’ people.
We believe that any organization can succeed by enriching and empowering its people.
Our own people empower our vision to be a premier global management consulting firm that Fortune 500 and leading organizations trust.
Essential Duties & Responsibilities: Work with AArete clients and internal customers to translate business needs into modern data architecture solutions Design and develop object and data models and data repositories structured for optimized management and high performance access.
Lead the implementation of enterprise data architectures Work closely with other Data Engineers, IT managers, and developers to ensure understanding and support of data architecture priorities Define, design, and build structured and unstructured databases and data pipelines to support analytics projects and transactional solutions Partner with various teams to define and execute data acquisition, transformation, processing and make data actionable for operational and analytics initiatives Review, test, and troubleshoot database structures and code Develop strategies for data acquisitions, archive, recovery, and implementation Create prototypes and proofs of concept for iterative development Deliver end-to-end analytics projects from data ingest through data visualization Develop, communicate, and present solutions architectures to both business and technical stakeholders Monitor, troubleshoot, and optimize performance of enterprise data pipelines and data repositories Provide technical guidance and support to developers, data engineers, and data administrators Lead and collaborate with internationally located teams Requirements: Bachelors Degree in Computer Science, or related discipline.
10 years of professional technical experience with 5 years in data engineering and analytics technologies including ETL (specifically SSIS and Azure Data Factory) and BI Expertise leading technical teams in the implementation of end-to-end enterprise data solutions Good knowledge of enterprise data environments, which include database design, metadata infrastructure, and business analytics Demonstrated experience in designing and implementing structured enterprise and analytic data engineering solutions Advanced database development skills and experience Knowledge of UML and object-oriented design In-depth knowledge with enterprise data implementation methodologies, and technologies with prior experience delivering full suite implementations.
Knowledge of Agile common frameworks Demonstrated experience and knowledge in database concepts and large-scale database design Experience developing flexible data ingest and enrichment pipelines to easily accommodate new and existing data sources Expert knowledge of Microsoft SQL Server as it relates to ingestion and loading of data Ability to communicate complex technical terminology, concepts and issues in terms understandable to technical and non-technical audiences Excellent oral and written communication skills Strong interpersonal skills to resolve problems in a professional manner by leading working groups to negotiate and create consensus Self-starter with an entrepreneurial spirit Experience masking and replicating large data sets, a plus Engineering unstructured datasets in a cloud environment, a plus Java / R/ Python, Big data, IoT, and Data science, a plus Healthcare, a plus