Data Solutions Architect

Quantanite; Singapore; Hybrid; SGD 90,000 - 120,000; Full time

Job summary

A customer experience solutions company in Singapore is looking for a Data Engineer to collaborate on creating scalable data warehouses and pipelines. You will lead efforts in data automation, integrate AI solutions, and ensure compliance with data governance. Ideal candidates will have over 8 years of IT experience and proficiency in SQL and Python. This role offers potential for remote work and competitive compensation.

Qualifications

• 8+ years of IT experience with at least 5 years in data engineering or architecture roles.
• Hands-on experience with data pipeline tools and cloud platforms.
• Proficient in SQL, Python, and ETL processes.

Responsibilities

• Collaborate with teams to analyze data from internal systems.
• Design and implement a scalable data warehouse with appropriate pipelines.
• Monitor data quality and optimize performance across the data ecosystem.

Skills

SQL

Python

ETL processes

Data modeling

Business Intelligence Tools

Education

Bachelor's or Master's degree in Computer Science or Data Engineering

Tools

Azure Data Factory

AWS Glue

Power BI

Tableau

Job description

Company DescriptionQuantanite is a customer experience (CX)solutions company that helpsfast-growing companiesand leading global brandsto transformand grow. We do thisthrough a collaborative andconsultative approach,rethinking business processes and ensuring our clients employ theoptimalmix of automationand human intelligence.We are an ambitiousteamof professionalsspread acrossfour continents and looking to disrupt ourindustry by delivering seamlesscustomerexperiencesforour clients,backed-upwithexceptionalresults.We havebig dreams,and are constantly looking for new colleaguesto join us who share our values, passion andappreciationfordiversity.Job DescriptionCollaborate with Workforce Management and Operational teams to analyze dataformats and structures from in-house Workforce Management systems or clientCRM/WFM systems Design and implement a scalable data warehouse or data lake with appropriate datapipelines. Ensure automated processing of operational data for generating standardized andcustomizable KPI matrices and dashboards. Lead the creation of systems that allow flexibility for client-specific rules andcalculations. Integrate AI/ML solutions for predictive analytics and business insights. Establish data governance and ensure compliance with security and regulatorystandards. Monitor data quality and optimize performance across the data ecosystem. Act as a technical leader, mentoring and managing a small team of data engineers. Provide regular updates to stakeholders and collaborate on defining long-term datastrategies.QualificationsEducation: Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.Experience: 8+ years of IT experience with at least 5 years in data engineering or architecture roles. Hands-on experience with data pipeline tools and cloud platforms (e.g., Azure Data Factory,Azure Databricks, AWS Glue). Proficient in SQL, Python, and ETL processes. Experience in designing data warehouses, data lakes, and creating dashboards using BI toolslike Power BI or Tableau. Familiarity with AI/ML technologies for analytics and predictive modeling. Strong understanding of data lifecycle management and compliance requirements.Mandatory Skills: Expertise in managing multi-source data integrations. Knowledge of industry-standard KPI frameworks and dashboarding techniques. Ability to handle client-specific customization requirements.Preferred Skills: Experience in BPO or IT Outsourcing environments. Knowledge of workforce management tools and CRM integrations. Hands-on experience with AI technologies and their applications in data analytics. Familiarity with Agile/Scrum methodologies.Additional InformationPreferred Skills: Experience in BPO or IT Outsourcing environments. Knowledge of workforce management tools and CRM integrations. Hands-on experience with AI technologies and their applications in data analytics. Familiarity with Agile/Scrum methodologies.Soft Skills: Strong analytical and problem-solving capabilities. Excellent communication and stakeholder management skills. Ability to thrive in a fast-paced, dynamic environment. Leadership qualities to mentor and guide a team effectively.,

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