OnX Canada is hiring a local Data Engineer / ETL Developer for Ottawa-local client in government domain, who can designing, building, and maintaining data infrastructure that supports the efficient extraction, transformation, and loading (ETL) of data from various sources. You will be serving as a subject matter expert in data management, integration, and processing and facilitates the creation of reliable and scalable data platforms that support informed decision-making.
• ** This role requires federal clearance (any level) so OWP (and PR with less then 5y of residency in Canada) do not qualify for this role.
• **Please do not send direct messages to a recruiter. Only candidates who have applied will be considered, and shortlisted candidates will be contacted for further discussion and intake.
Location: on-site in Ottawa (Fairmont Ave) - remote is NOT possible/must be committed to a regular hybrid model
Duration: initial 6m CONTRACT with very high probability of switching to a permanent FT eventually
Tentative start date: between Dec2023- and Feb2024
Hours per week: 40 (Monday to Friday day shift schedule)
MUST_HAVE Requirements (general):
• Able to work in Ottawa office on a regular basis (rotational hybrid model)
• Have a valid federal security clearance (any level), or past experience of working for CAN government organizations, or proven eligibility for security clearance (over 10y in Canada, clear criminal record, Canadian citizenship)
• Commitment for a technical screening, and tech interviews (likely, on-site)
• Commitment to converting to a Perm/ F/T after initial contract
• 4-year university degree in Information Technology, Computer Science, Computer Engineering, or a related discipline
MUST_HAVE Requirements (technical):
• Must have: 5+years’ work experience in a Data Analytics environment with progressively more technical responsibilities in an engineering role
• Must have advanced SQL /query development in SQL
• Strong data warehousing/data modeling (Logical and physical data models)
• Strong technical expertise in ETL processes, data pipelines and workflows.
• Must have good Python coding skills (for automation and troubleshooting pipelines and data processing)
• Streamsets– experience or ability to learn and adapt to it quickly
• Working with cloud computing platforms (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
Knowledge, skills, and proficiency
Designing and implementing:
• Real-time data processing pipelines
• Database solutions using technologies such as MySQL, PostgreSQL or SQL Server.
Designing and creating:
• Utilization of tools such as Apache Spark, Hadoop, and other big data technologies.
• Designing, building, and supporting data warehouses, data hubs and other data storage and processing systems.
• Project implementation analysis and support in data management systems, data integrity and security as it relates to environmental business systems.
• Develop scripts, applications and APISs to automate data processing tasks using programming languages such as SQL, Python, Java, Scala, shell scripting, JavaScript
• Machine Learning concepts and tools (R, Python, Jupyter Notebook).
• English – complete fluency in oral, reading, and writing.
• Data warehousing and data modeling principles and practices.
• Documenting data pipelines processes, data models and data dictionaries.
• Designing, building, and supporting data warehouses, data hubs and other data storage and processing systems.
• Windows and Linux operating systems and their commands, on prem and cloud environments.
• Programming languages, such as Python, Java, Scala, shell scripting, JavaScript.
• Virtual platforms, MS Office Suite, including the use of virtual platforms for conducting meetings and/or presentations
• Understanding of data security and privacy regulations to support implementation of appropriate security measures to protect data
• Knowledge and experience of data analytics development lifecycles/methodologies. such as Agile or other rapid application development methods
• Strong knowledge of data and statistical methods, tools, and operationalizing analytic models
Major 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 techniques
- Design, 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 needs
- Design 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.
• Serves as a subject matter expert in data management, integration, and processing and facilitates the creation of reliable and scalable data platforms that support informed decision-making.
- Supports the translation of business requirements for data acquisition/manipulation and provides detailed specifications to end users
- Proactively identify analytical opportunities and provide recommendations that improve all elements of the data analysis process and increase analytical capacity throughout the organization.
- Creates documentation of data engineering activities and data dictionaries to support end-users of data systems.
- Maintains knowledge of current trends and best practices respecting data engineering, data science, and data privacy regulations.
• Collaborates with cross-functional teams to enable members and the community with access to accurate, reliable, and timely data.
- Work with data analysts and data scientists to ensure that data is properly structured and available for analysis.
- Collaborate with stakeholders across the police service to design and implement race data collection strategies.
- Proactively establishes partnerships, identifies opportunities, and makes recommendations that increase analytical capacity throughout the organization and with our community.
- Provides supervision, guidance, and training to analysts, researchers, and others in the organization on data analytics.
DESIRED QUALIFICATIONS:
• Fluency in French
• Experience with Power BI desktop, mobile and service offerings, or other similar business intelligence tools.
• Experience with geospatial analysis using the ArcGIS platform
