Data Analytics Lead, GR TMRW

UOB•Phoenix, AZ

About The Position

We are seeking a highly skilled and passionate Data Analytics professional to join our growing team. This is a unique opportunity for an individual who thrives at the intersection of data engineering, platform development, and business intelligence. You will play a pivotal role in shaping our data strategy, building robust data solutions, and transforming raw data into actionable insights that drive critical business decisions. What You'll Do: 1. Data Platform Development: Design, build, and maintain scalable and robust data platforms and pipelines to support various data initiatives. Establish best practices for data governance, data quality, and data security. Collaborate with engineering and product teams to integrate new data sources and improve data accessibility. 2. Data Engineering: Define, Design, and maintain ETL processes to ingest, transform, and load data from diverse sources into our data warehouse/data lake. Ensure data integrity, accuracy, and reliability across all data pipelines. Troubleshoot and resolve data-related issues, ensuring minimal disruption to data availability. 3. Data Analysis & Insights Generation: Conduct in-depth data analysis to identify trends, patterns, and anomalies in large datasets. Develop compelling dashboards, reports, and visualizations to communicate key insights to stakeholders across various departments. Translate complex data findings into clear, concise, and actionable recommendations for business improvement and strategic decision-making. Proactively identify opportunities for data-driven optimization and innovation. 4. Cross-functional Collaboration & Leadership: Partner closely with business stakeholders to understand their analytical needs and translate them into technical requirements. Mentor junior data professionals (if applicable to seniority). Champion a data-driven culture within the organization.

Requirements

8-10 years of experience in data analytics, data engineering, business intelligence, or related field.
Proven experience in building and maintaining data platforms and pipelines from scratch or significantly enhancing existing ones.
Demonstrated ability to generate actionable business insights from complex datasets.
Strong proficiency in SQL for data querying, manipulation, and analysis.
Experience with a cloud data platform (e.g., AWS Redshift, Google BigQuery, Azure Synapse, Snowflake).
Proficiency in at least one programming language is commonly used for data engineering and analysis (e.g., Python).
Experience with data visualization tools (e.g. Power BI, Qlik Sense).
Understanding of data warehousing concepts (e.g. dimensional modeling).
Execute tasks within Agile/Waterfall frameworks, eg, design of scripts based on functional requirements, execution of test cases and defect fixes in JIRA, sharing of llearnings and best practices in Confluence, etc.
Excellent analytical and problem-solving skills with a keen eye for detail.
Strong communication and presentation skills, with the ability to articulate complex technical concepts to non-technical audiences.
Ability to work independently and as part of a collaborative team.
Proactive, self-motivated, and eager to learn new technologies.
Business acumen and the ability to connect data insights to business outcomes.

Responsibilities

Data Platform Development: Design, build, and maintain scalable and robust data platforms and pipelines to support various data initiatives.
Establish best practices for data governance, data quality, and data security.
Collaborate with engineering and product teams to integrate new data sources and improve data accessibility.
Data Engineering: Define, Design, and maintain ETL processes to ingest, transform, and load data from diverse sources into our data warehouse/data lake.
Ensure data integrity, accuracy, and reliability across all data pipelines.
Troubleshoot and resolve data-related issues, ensuring minimal disruption to data availability.
Data Analysis & Insights Generation: Conduct in-depth data analysis to identify trends, patterns, and anomalies in large datasets.
Develop compelling dashboards, reports, and visualizations to communicate key insights to stakeholders across various departments.
Translate complex data findings into clear, concise, and actionable recommendations for business improvement and strategic decision-making.
Proactively identify opportunities for data-driven optimization and innovation.
Cross-functional Collaboration & Leadership: Partner closely with business stakeholders to understand their analytical needs and translate them into technical requirements.
Mentor junior data professionals (if applicable to seniority).
Champion a data-driven culture within the organization.