Senior Data Analyst at Great Eastern Life Assurance Co Ltd

Cuenca, Azuay, Ecuador -

Full Time

Start Date

Immediate

Expiry Date

17 Aug, 26

Salary

0.0

Posted On

19 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Visualization, SQL, Tableau, PowerBI, Qlikview, Data Storytelling, Requirements Gathering, Data Modeling, Python, Spark, Hadoop, Big Data Ecosystems, Business Intelligence, Analytical Thinking, Stakeholder Management, Data Analysis

Industry

Insurance

Description

The Senior Data Analyst is responsible to work closely with business stakeholders to transform enterprise data into actionable insights. This role is critical in enabling business performance through strong analytical thinking, sound business acumen, and the ability to communicate insights via compelling data storytelling. The role entails conducting deep dive analyses and developing best practice data visualizations and dashboards using appropriately aggregated data sources. The Senior Data Analyst is expected to work independently to deliver analytics projects, collaborate closely with key stakeholders, and apply the necessary technical expertise to implement analytics solutions that position data as a strategic asset. Collaborate with business stakeholders to understand requirements and translate data into meaningful actionable insights Perform deep‑dive analyses to identify trends, risks, and opportunities that support strategic decision‑making Design, build and enhance visual analytics assets to ensure continued relevance and usage of the dashboards by business users for making informed decisions Maintain data models to ensure all data are up to date with data accuracy and integrity Collaborate with business to align logics of key metrics, and to ensure code logics correctly reflect latest business definitions Work closely with business stakeholders and data engineers to communicate data requirements, and validate quality of data products Work with data engineers to define the key data pipelines required to support Business Ensure all analytics project undertaking comply with both internal and external policies, guidelines and regulations Takes accountability in considering business and regulatory compliance risks and takes appropriate steps to mitigate the risks. Maintains awareness of industry trends on regulatory compliance, emerging threats and technologies in order to understand the risk and better safeguard the company. Highlights any potential concerns /risks and proactively shares best risk management practices. Bachelor of Science degree in Business Analytics, Statistics, Economics, Actuarial Science, Data Science, Computer Science, Mathematics or equivalent disciplines that focuses on extensive use of data for analysis A minimum 5 years of experience participating in business intelligence and analytics projects as an individual contributor required A minimum 5 years of experience in data visualization tools (Tableau / PowerBI / Qlikview) is required A minimum 5 years of experience in SQL programming and standard MS Office applications is required Ability to analyze, identify, visualize and describe key trends within large datasets Hands-on experience with large volumes of data using SQL, Spark, Hadoop, or other big data ecosystems is preferred Good at requirements gathering, multitasking and work prioritization and being able to deliver work timely under pressure Understanding of banking, insurance and financial services is preferred Curiosity & a real passion for understanding “why?” Creativity to see possibilities within the data & translate into compelling stories, decision and actions for non-technical business users Strong communication skills and ability to influence the business to take action using data Knowledge of Python is preferred High level of integrity, takes accountability of work and good attitude over teamwork. Takes initiative to improve current state of things and adaptable to embrace new changes

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Responsibilities

Transform enterprise data into actionable insights through deep-dive analyses and the development of visual dashboards. Collaborate with stakeholders and data engineers to define data requirements and ensure the integrity of data models.