Reporting and Analytics Developer

USER EXPERIENCE RESEARCHERS PTE. LTD.; Singapore; On-site; SGD 100,000 - 180,000; Full time

Job summary

USER EXPERIENCE RESEARCHERS PTE. LTD. in Singapore is seeking a data engineer to design and optimize data pipelines and data warehouses to support analytics and product data needs.

You will work with cross-functional teams including PMs, engineers, and designers to build scalable data-driven solutions, leveraging cloud services and modern ETL tools.

The role emphasizes collaboration, CI/CD, and hands-on development of backend APIs and data processing components.

Qualifications

• Proficient in data cleaning and transformation (SQL, pandas, R) for data accuracy.
• Experience building ETL pipelines using SSIS, AWS DMS, Python, Lambda and Glue.
• Skilled in database design with SQL, PostgreSQL, MongoDB, MySQL, and more.
• Familiar with cloud platforms (GCP, AWS, Azure) and big data tools.
• Experience with REST APIs, web scraping, and data governance basics.

Responsibilities

• Design, develop, and deploy data tables, views, and marts in data warehouses, data lakes, and data virtualization.
• Perform data extraction, cleaning, transformation, and data flow management, including web scraping.
• Build scalable batch and real-time data pipelines with processing frameworks.
• Integrate data silos in a scalable, compliant manner.
• Collaborate with PMs, Data Architects, Business Analysts, Frontend Devs, Designers, and Data Analysts to build data-driven products.
• Develop backend APIs and support databases for applications.
• Work in an Agile CI/CD environment.
• Collaborate with fellow developers through pair programming and code reviews.

Skills

SQL

Pandas

Python

ETL pipelines

Data pipelines

REST APIs

Web scraping

Big data

Scripting

Linux

Windows

Data modeling

Cloud platforms

Spark

Hadoop

Tools

SSIS

AWS DMS

AWS Lambda

ECS

EventBridge

AWS Glue

Spring

BeautifulSoup

CasperJS

PhantomJS

Selenium

Node.js

Airflow

Snowflake

Databricks

Job description

Key Responsibilities

• Design, develop, and deploy data tables, views, and marts in data warehouses, operational data stores, data lakes, and data virtualization.
• Perform data extraction, cleaning, transformation, and data flow management. Web scraping may also be a part of the work scope in data extraction.
• Design, build, launch, and maintain efficient and reliable large-scale batch and real-time data pipelines with data processing frameworks.
• Integrate and collate data silos in a manner that is both scalable and compliant.
• Collaborate with Project Managers, Data Architects, Business Analysts, Frontend Developers, Designers, and Data Analysts to build scalable, data-driven products.
• Be responsible for developing backend APIs and working on databases to support applications.
• Work in an Agile environment that practices Continuous Integration and Continuous Delivery.
• Work closely with fellow developers through pair programming and code review processes.

Experience and Skills Needed

• Proficient in general data cleaning and transformation (e.g., SQL, pandas, R, etc.) to ensure data accuracy and consistency.
• Proficient in building ETL pipelines (e.g., SQL Server Integration Services (SSIS), AWS Database Migration Service (DMS), Python, AWS Lambda, ECS Container Tasks, EventBridge, AWS Glue, Spring).
• Proficient in database design and various databases (e.g., SQL, PostgreSQL, AWS S3, Athena, MongoDB, PostGIS, MySQL, SQLite, VoltDB, Cassandra, etc.).
• Experience in cloud technologies such as GCP, GCC (i.e., AWS, Azure, Google Cloud).
• Experience and passion for data engineering in a big data environment using cloud platforms such as GCP, GCC (i.e., AWS, Azure, Google Cloud).
• Experience with building production-grade data pipelines and ETL/ELT data integration.
• Knowledge of system design, data structures, and algorithms.
• Familiar with data modelling, data access, and data storage infrastructure such as Data Marts, Data Lakes, Data Virtualization, and Data Warehouses for efficient storage and retrieval.
• Familiar with REST APIs and web requests/protocols in general.
• Familiar with big data frameworks and tools (e.g., Hadoop, Spark, Kafka, RabbitMQ).
• Familiar with W3C Document Object Model and customised web scraping (e.g., BeautifulSoup, CasperJS, PhantomJS, Selenium, Node.js, etc.).
• Familiar with data governance policies, access control, and security best practices.
• Comfortable with at least one scripting language (e.g., SQL, Python).
• Comfortable working in both Windows and Linux development environments.
• Interest in being the bridge between engineering and analytics.

Bonus Experience (Added Advantage)

• Experience building data engineering pipelines that require integration with search indexes.
• Experience with Airflow and RDBMS integration and implementation (e.g., MySQL).
• Experience with either Snowflake, Databricks, or an equivalent provider