Data Engineer, Associate/Senior Associate,

EY; Singapore; On-site; SGD 70,000 - 100,000; Full time

Job summary

EY is looking for a Data Engineer in Singapore, responsible for designing, building, and maintaining ETL/ELT pipelines for structured and unstructured data. The role requires collaboration with data scientists and stakeholders to ensure the quality and availability of data.

Candidates should have 2–6 years of experience, proficiency in SQL and Python, and familiarity with cloud platforms and data orchestration tools. A Bachelor's or Master's degree in a relevant field is required.

Qualifications

• 2–6 years of experience in data engineering or related roles.
• Hands-on experience with data warehouses such as Snowflake, BigQuery, or Redshift.
• Knowledge of streaming data frameworks (Kafka, Spark Streaming, Flink) is a plus.

Responsibilities

• Design, build, and maintain ETL/ELT pipelines for structured and unstructured data.
• Develop and optimize data workflows for advanced analytics and reporting tools.
• Collaborate with data stakeholders to ensure data quality and availability.
• Troubleshoot and resolve data issues in real-time and batch pipelines.

Skills

SQL

Python

Scala

Data orchestration tools

Cloud platforms (AWS, Azure, GCP)

Data warehouses (Snowflake, BigQuery, Redshift)

Data modeling

CI/CD

Education

Bachelor's or Master's degree in Computer Science, Engineering, or related field

Tools

Apache Airflow

DBT

Luigi

Job description

Your key responsibilities

• Design, build, and maintain efficient, reusable, and scalable ETL/ELT pipelines for structured and unstructured data.
• Develop and optimize data workflows to support advanced analytics, machine learning models, and reporting tools.
• Collaborate with data scientists, analysts, and business stakeholders to gather requirements and ensure data quality and availability.
• Work with cloud and on-prem data platforms (e.g., AWS, Azure, GCP, Hadoop, or on-prem SQL/NoSQL systems).
• Ensure data integrity, governance, and security best practices across pipelines and data lakes/warehouses.
• Troubleshoot and resolve data issues and performance bottlenecks in real‑time and batch pipelines.
• Monitor job performance and implement automation and alerting for data operations.
• Contribute to documentation, code reviews, and development best practices.

Skills and attributes for success

• 2–6 years of experience in data engineering or related roles.
• Proficient in SQL, Python, or Scala for data processing.
• Experience with data orchestration tools like Apache Airflow, DBT, or Luigi.
• Familiarity with cloud platforms (AWS Glue, Azure Data Factory, GCP Dataflow, etc.).
• Hands‑on experience with data warehouses such as Snowflake, BigQuery, or Redshift.
• Understanding of data modeling, normalization, and data warehousing concepts.
• Exposure to CI/CD, version control (Git), and agile development practices.

To qualify for the role, you must have

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• Knowledge of streaming data frameworks (Kafka, Spark Streaming, Flink) is a plus.
• Experience working in consulting or client‑facing environments (for Senior Associate roles).
• Certifications in AWS/Azure/GCP or specific data tools.