ApacheAzureDockerETLGradleHadoopHDFSMavenMS SQL ServerNoSQLPythonSparkSQLSSISSwiftTableauMachine LearningELTData LakeAnalyticsBIBusiness IntelligencePower BIDatabricksTeamCityBambooLambdaSQL ServerGitSource Control
About this role
Role Overview
Play an integral role in our delivery practice as we execute on enterprise level client engagements through our various industry specializations
Engage directly with clients and drive the implementation and successful end user experience of analytics solutions; execute on engagements and collaborate with the client and delivery team to ensure that any applicable milestones and deliverables are met on time and on budget
Design and develop industry-specific data models for client projects in industries such as Natural Resources, Finance, Manufacturing and Distribution, and Retail
Work with other engineers to enhance data models and improve data query efficiency; create complex data queries to facilitate ad hoc and exploratory analytics
Build real-time data capture and transformation functionality across all products and build out technology stack for Business Intelligence and Data Warehouse
Clean data: review for data inconsistencies and identify opportunities to improve data collection process; Wrangle/Munge data: transform or map data from one raw data form into another format with the intent of making it more appropriate and valuable for analytics
Develop, construct, test and maintain architectures such as databases and large-scale data processing systems; design, construct, install, test and maintain highly scalable data management systems
Employ a variety of languages and tools (e.g. scripting languages) to marry systems together
Build or recommend data visualization tools and business intelligence tools such as interactive dashboards and automated reports, to enable leaders to make swift, fact-based decisions
Remain up to date of development technologies, both current and future in order to deliver state-of-the-art Analytics solutions for our customers
Requirements
Post-secondary education in engineering or computer science or equivalent work experience
Good experience working with Azure Databricks, Azure Data Factory and Azure Data Lake
Programming experience in Python
Strong attention to the quality of work delivered (attention to detail)
Able to adapt quickly to changing client requirements
Experience using the Apache Hadoop ecosystem (Spark, Data Lake, Hive, HDFS, Impala) to tackle "big data" problems (asset)
Knowledge of ETL, ELT, Lambda and Kappa data architectures (asset)
Experience with the Microsoft SQL Server Analytics stack including: Core SQL, SSIS, SSRS, SSAS (asset)
Experience working with SQL and NoSQL databases (asset)
Knowledge of Continuous Integration and Source Control systems (e.g. Gradle, Maven, Bamboo, TeamCity, Git ) (asset)
Data Visualization experience in Power BI, Tableau, or similar (asset)
Exposure to data science, machine learning or statistics (asset)
Some experience using Docker (asset)
Tech Stack
Apache
Azure
Docker
ETL
Gradle
Hadoop
HDFS
Maven
MS SQL Server
NoSQL
Python
Spark
SQL
SSIS
Swift
Tableau
Benefits
flexible benefits from day one
a market leading personal time off policy
reimbursement for wellness initiatives that fit your lifestyle