Technical Business Analyst / Data :
Location: Limerick or Dublin
Hybrid
One of our large financial clients is looking for a Data Analyst for Data Mesh/Derivatives Data Modernization/Cloud Enablement program who is self-motivated, creative and proactive, to work successfully in a fast-paced environment including multiple platforms, architectures, and diverse technologies. The individual will work closely with various stakeholders throughout the software development lifecycle. The individual should have a strong understanding of agile processes and will be responsible for collaborating closely with cross-functional teams to elicit, analyze, and refine user requirements.
Looking for a senior data analyst who collects, cleans, analyzes, and interprets data from various sources to identify patterns and trends, then presents findings through visualizations and reports to inform business decisions, requiring strong analytical skills, proficiency in data manipulation tools like SQL, and excellent communication to effectively convey insights to stakeholders.
Responsibilities:
1. Analyse complex business problems and identify potential solutions.
2. Develop and implement solutions to complex problems.
3. Translate requirements into clear user stories and acceptance criteria within an iterative development process.
4. Data Collection and Cleaning:
o Gathering data from multiple sources, cleaning and structuring it to ensure accuracy and quality for analysis.
o Analyze data from science, engineering, business, and other sources.
5. Exploratory Data Analysis (EDA):
o Investigating data to discover patterns, relationships, and anomalies through statistical techniques.
6. Report Generation:
o Developing and presenting comprehensive reports with key findings and actionable recommendations to stakeholders.
7. Data Visualization:
o Creating compelling visual representations of data using charts, graphs, and dashboards to communicate insights clearly.
o Applying statistical methods to interpret data and extract meaningful insights.
8. Agile Ceremonies:
o Facilitate sprint planning meetings to define sprint goals and user stories.
o Participate in daily stand-ups to track progress and identify potential roadblocks.
o Contribute to sprint retrospectives to identify areas for improvement.
o Actively participate in backlog grooming sessions to refine and prioritize user stories.
9. Communication & Collaboration:
o Effectively communicate business requirements to the development team and stakeholders.
o Act as a bridge between business and technical teams to ensure alignment.
10. Work with different departments to understand their data needs and translate analysis into business solutions.
11. Collaborate with the Scrum Master to manage the agile process and resolve impediments.
12. Collaborate with the Product Owner to maintain a well-structured and prioritized product backlog.
Required Skills:
1. Great analytical, critical thinking and problem-solving abilities.
2. Data analysis, Process modeling, SQL, User Acceptance Testing (UAT), and Regression Testing.
3. Adaptable and capable of working in fast-paced environments.
4. Five or more years of experience in a Technical Business or Data Analyst role.
5. Agile Methodology:
o Deep understanding of Agile principles, practices (Scrum, Kanban), and tools.
6. Requirement Analysis:
o Proven ability to elicit, analyze, and document complex business requirements.
7. User Story Writing:
o Excellent skills in crafting clear, concise, and well-defined user stories with acceptance criteria.
8. Communication & Collaboration:
o Excellent written and verbal communication skills.
o Strong interpersonal skills to effectively collaborate with diverse teams and stakeholders.
o Effectively presenting complex data insights to both technical and non-technical audiences.
o Superior presentation, negotiation, strong management and organizational skills.
9. Technical Skills: Proficiency in SQL, data manipulation tools (Excel, Python, Alteryx or any ETL tools), data visualization software (Power BI, Sigma, or Tableau), Databases – Sql server, Oracle, Azure or Snowflake.
10. Statistical Knowledge: Understanding of statistical concepts like hypothesis testing, regression analysis, and probability.
11. Analytical Thinking: Ability to identify patterns, trends, and relationships within complex datasets.
12. Problem-Solving: Identifying issues within data and proposing solutions to address them.
13. Attention to Detail: Ensuring data accuracy and consistency throughout the analysis process.
14. Technical Knowledge: Basic understanding of software development technologies and processes.
Education:
1. Bachelor's degree in a relevant field such as business, finance, information technology, or a related discipline.
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