Technical Data Analyst - banking area

Technical Data Analyst in Banking

Key Responsibilities:

The role of the Analytical Technical Data Analyst focuses on driving initiatives within the Analytical Data Program to support the division in becoming more data-centric.

• Gather and prioritize technical data needs for the Analytical team.
• Develop and implement a data framework for Analytical, offering technical solutions to stakeholders.
• Ensure compliance, adoption, and ongoing enhancement of data standards, policies, and procedures.
• Offer expertise to various teams by assisting in accessing critical data and resolving data quality issues using Collibra.
• Collaborate with IT and system teams to establish data sharing agreements and define access protocols.
• Advise data producers and stakeholders on optimizing data accessibility for key areas like transaction monitoring, KYC, sanctions, screening, and fraud.
• Identify optimal sources of master data based on business requirements.
• Lead product approval committees and make data-related decisions.
• Understand and manage data structures, providing technical knowledge as needed.
• Promote collaboration between the Data Governance team, key business functions, and IT to ensure successful data initiatives.
• Design ETL processes to support data extraction and create a robust data governance framework.
• Drive the organization’s transformation towards being data-driven.

Essential Qualifications:

• Significant experience working as a Technical Data Analyst or a similar position within a Data or IT department.
• Strong knowledge of data governance, key data elements, and technical asset models, along with experience implementing changes for data management.
• Oversee data access, monitor data entry, and manage data maintenance for owned data assets.
• Enforce annual standards for master data domains.
• Experience in the analytical business sector.
• Analytical mindset to troubleshoot data issues and propose solutions for data producers.
• Familiarity with Collibra DQ is a plus.
• Hands-on experience with programming languages like Python, SQL, Scala, or BigQuery for data analysis.
• Understanding of data solutions on cloud platforms and experience with migrating data from on-premise environments.
• Collaborate with subject matter experts to identify data requirements and create logical data models.
• Knowledge of JSON and/or XML.
• Ability to leverage data as a business asset.

Required Knowledge, Skills, and Experience:

• Comprehensive understanding of Financial Crime Prevention is advantageous.
• Awareness of challenges faced by banks in managing data.
• Familiarity with Google Cloud BigQuery is a plus.
• Experience handling large and complex data sets.
• Ability to create detailed documentation on business terms, data lineage, transformation rules, and processes.
• Hands-on experience with Sparx, Scala, and Python.
• Proven track record in conducting data quality and integrity assessments.
• Excellent communication skills for engaging both technical and business stakeholders.
• Ability to work effectively across teams and locations.
• Experience using Collibra tools for data-sharing agreements and GDPR compliance assessments.
• Passion for cloud-based technologies and delivering business value.