Apex Systems is partnering with a top Canadian Bank to hire for a Business Data Analyst who can be the bridge between the client's business teams and the technical teams who perform Data Analysis. We are looking for someone with 5+ years of experience in Data Analytics, improving data governance processes supporting data transformation, data structures, metadata, etc.

Contract: 6 months, likely to extend (multiple year potential)

Start Date: ASAP

Location: Toronto, ON (minimum 3 days per week onsite)

Business Consultant, Data Analysis (CIBC)

The individual will assist the Client Data team with the following:

• Analyze, query and manipulate data according to understand currently defined business rules and procedures.
• Analyze current state data quality controls to design specification (source-to-target) and expected/anticipated behaviors, identifying quality issues and recommending solutions
• Assist in the design of quality edit checks, test plans, etc. to ensure data quality objectives are met, as well as participate in cross-functional team engagement
• Provide accurate and appropriate interpretation of data, applying knowledge to evaluation, analysis, and interpretation of data
• Provide support for analysis and research into our client data structure, maintenance, performance, and modelling.
• Assist in defining, understanding and implementing the policies & standards for cloud native data as it pertains to structured, semi- and unstructured data so that it aligned to the the role that is defined by enterprise data governance for migrations from cloudera native data management to Azure, with focus on client data domain
• Analyze data for compliance to design specification (Prem-to-Azure) and expected/anticipated behaviors, identifying quality issues and recommending solutions
• Develop complex data quality audits using SQL to identify possible data issues coming into Purview, abstract data, and clearly summarize and present data
• Collaborate with database developers to improve data collection and storage processes during migration from Prem to cloud to Identify incorrect data, documenting issues, patterns and gaps in the data and/or system
• Document data process flows to support data sourcing & lineage Data Modelling methodologies & tools
• Manage documentation related to data quality (data standards, definitions ( technical and business), DQ documents such as metadata, data dictionaries, checklists, guidelines, manuals, etc.)
• Build, update and maintain dashboards that report on key data quality metrics related to banks client data domain
• Ensures data integrity by implementing quality assurance practices, gathering and entering missing data, and resolving anomalies.
• Assist in tracking, mining, and analyzing data to recommend KPI's for client data domain in order to build Data Quality Rules & KPIs
• Evaluating system performance and design within Purview, as well as its effect on data quality.
• Perform root cause analysis on data issues and make long term recommend on data quality controls to resolve gaps/issues and suggest ways to improve systems and database designs.
• Running data queries to identify coding issues and data exceptions, as well as cleaning data.
• Facilitate Data cleansing and enrichment through data de-duplication and construction
• Performs logical edit checks on the data and reviews trends in the data to identify potential errors.
• Performs other related quality control tasks to identify discrepancies and violations.
• Performs quality control activities on the collected data, requests clarifications as appropriate.
• In-depth knowledge of data quality testing in order to verify the accuracy and completeness of information within various systems with Purview
• Perform ad-hoc Data extraction and archival; Managing Data life-cycle

Knowledge/Technical Skills:

Expertise in using Hadoop, Spark, Pig, Hive technologies, Data Ingestion in Data Lake, Data Storage on key Cloud providers (Azure), Data Retrieval on Big Data platforms and Interfacing Data Science and Data Visualization tools on Big Data platforms.

• A good overview of Azure cloud technologies: Hands on with Azure Cloud tool like Purview, Azure Data factory, Azure Data Bricks, ADLS and overall Azure cloud
• Comprehensive understanding of Data Modeling, Big Data Platforms (e.g. Cloudera, Azure, etc.), Data Migration and Quality (using ETL e.g Informatica, DataMirror Alteryx ), MySQL/NoSQL, Linus Scripts
• Proficient in data migration between different sources / targets on-prem and Cloud, of varying data repository technologies, DB2, Oracle, SQL Server and Data Lakes
• Data Warehouse knowledge/experience
• Knowledge of banking regulations and procedures, data management processes and database-related technical skills.
• Must Have strong data management and governance skills knowledge i.e. Knowledge of theories, principles, and methods utilized in the development of data quality improvement metrics
• Sound knowledge current and emerging data management and analysis methods.
• Knowledge of best practices in data analysis. i.e. Advance understanding of the collection and management of metadata (as it relates to the governance of data and data quality)
• Design and develop dashboards and data visualizations that tell a story from complex data using tools such as Alteryx, Power BI, Tableau
• Sound to advanced knowledge of banking standards, infrastructure, architecture and technology from a design/support/ solutions perspective.

Experience

Proven track record of having built / improved data governance processes supporting data transformation, data structures, metadata, data quality controls, dependency and workload management.

• Experience with Data Management, Data Governance, or Data Quality. Proven experience of having worked and data quality skills in:
• Data Profiling, quality rules definition
• Data Discovery
• Data quality measurement and metric generation, and aggregation into quality performance indicators
• Root cause analysis
• Good knowledge of data quality concepts, data quality trends and other tools in market such as Alteryx, Data Mirror, Milo
• Skills in data profiling and data analysis
• Expertise in developing KPI’s and business rules related to data quality
• Ability to work with Technical and Non-Technical business owners
• Experience in working with Azure Cloud Data Analytics
• Data Warehouse Tools
• Data Conversion & Migration
• Master Data Management
• Metadata Management
• Data Management and Integration during migration projects
• Experience and knowledge with data quality life cycle, data trending, dashboard and reporting with tools such as Cognos, PowerBI and Tableau, Data Mesh concepts
• Hands on working experience in dealing with large volume data quality analysis, data profiling, data masking, transformation & cleansing, data extraction & loading from heterogeneous data sources to Cloud e.g: data tokenization, standardization, matching and validation
• Experience with data quality and ETL technologies, programming and tools such as Informatica Data Quality, Data Mirror or OEDQ
• Experience with data quality and data migration principles and best practices
• Experience and knowledge with Azure Cloud Computing, Azure Service Model (e.g. IaaS, PaaS) and Azure storage technologies
• Successfully have examined complex data to optimize the efficiency and quality of the data being collected, resolve data quality problems, and collaborate with database developers to improve systems and database designs.
• Should have experience with, and understanding of, implementing and measuring Data Quality and Controls