Int Data Engineer to design, build and maintain data infrastructure

Our valued client is looking for an Int Data Engineer to design, build and maintain data infrastructure. initial 3-6 month contract hybrid in Ottawa with possibility for conversion to full time permanent. (min 2 days a week onsite) Responsibilities:Designing, building, and maintaining data infrastructure that supports the efficient extraction, transformation, and loading (ETL) of data from various sources.Develops ways to increase the usability of data through changes in business process and/or data cleansing techniquesDesign, build, and maintain data pipelines and ETL processes using tools such as Streamsets, Apache Spark, Hadoop, and other big data technologies.Develop and maintain data infrastructure including data warehouses and other data storage solutions to support business intelligence and reporting needsDesign and implement data security measures to protect sensitive data.Develop and maintain data quality control processes to ensure the accuracy, reliability, and accessibility of data to all stakeholders.Monitors system performance of scheduled ETL batches, and streaming data process and ensures all systems are working at an acceptable standard and that data pipelines are scalable, repeatable, and secure.Performs data migration between development, UAT, and production systems, and plans and coordinates these data migrations.Analyzes and troubleshoots technical issues quickly to resolution, working with internal ITS sections and software vendors, when required.Must Have Skills:5+ years experience in a Data Analytics environment with progressively more technical responsibilities in an engineering roleDesigning and creating: ETL processes, data pipelines and workflows.Logical and physical data models using data modelling best practices.Develop scripts, applications and APISs to automate data processing tasks using programming languages such as SQL, Python, Java, Scala, shell scripting, JavaScriptDesigning, building, and supporting data warehouses, data hubs and other data storage and processing systems.Nice to Have Skills:Experience with cloud computing platforms such as Azure and being familiar with setting up and managing cloud-based data storage and computing environments.Working with stream processing frameworks such as Apache Kafka or Streamsets Designing and implementing:Real-time data processing pipelines using these tools.Database solutions using technologies such as MySQL, PostgreSQL or SQL Server. Project implementation analysis and support in data management systems, data integrity and security as it relates to environmental business systems.Machine Learning concepts and tools (R, Python, Jupyter Notebook).Utilization of tools such as Apache Spark, Hadoop, and other big data technologies.