Core Engineering, Data Software Engineer, Associate, Singapore

GOLDMAN SACHS SERVICES (SINGAPORE) PTE. LTD.; Singapore; On-site; SGD 80,000 - 120,000; Full time

Job summary

Goldman Sachs seeks a skilled Data Software Engineer in Singapore to design scalable data systems and pipelines. The candidate will focus on data modeling, quality, and governance while collaborating with cross-functional teams to ensure data integrity. This role offers a chance to leverage advanced data technologies and contribute to impactful business outcomes.

Qualifications

• Minimum 3 years of experience in software engineering or data engineering.
• Proficiency in Python, Java, or Scala.
• Strong knowledge of SQL and relational databases.

Responsibilities

• Design and maintain scalable data pipelines for large datasets.
• Ensure data governance standards and security measures are implemented.
• Develop and optimize data models tailored to business needs.

Skills

Data modeling

Data governance

Data pipeline development

Problem-solving

Analytical skills

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science

Tools

PostgreSQL

AWS

Apache Airflow

Hadoop

Job description

Goldman Sachs employs thousands of engineers across many divisions. We write software that powers every aspect of our business. It's no surprise that we collect and analyze vast amounts of data relating to the efficiency of our development processes, the value that we drive through software, and the effectiveness of how we leverage our internal tooling and services to empower development. Our data allows our internal businesses to optimize, focus their attention and manage costs. It allows us to assess the impact and performance of developer productivity initiatives, cost saving initiatives, and manage our huge software inventory.

What We Need

We are seeking a highly skilled Data Software Engineer to design, implement, and maintain robust data systems and pipelines that empower our organization to leverage data effectively. The ideal candidate will come from a software engineering background, with commercial development experience in one or more object-oriented languages (Python, Go, Java, C#). Knowledge of data modeling, pipeline construction, data normalization and sanitization, and data governance would be highly advantageous. They will collaborate with cross-functional teams to ensure the availability, quality, and security of data to support business objectives.

Key Responsibilities

1. Data Pipeline Development

• Design, build, and maintain scalable and efficient data pipelines for processing and transforming large datasets.
• Ensure pipelines are optimized for reliability and performance.

2. Data Modeling and Architecture

• Develop and maintain logical and physical data models tailored to business needs.
• Optimize data storage solutions for scalability and performance.

3. Data Quality and Sanitization

• Implement processes for data normalization, deduplication, and cleaning to ensure high-quality datasets.
• Identify and resolve data inconsistencies, errors, and anomalies.

4. Data Governance and Security

• Establish and enforce data governance standards, including policies for data access, compliance, and privacy.
• Implement security measures to protect sensitive data and ensure compliance with regulatory requirements.

5. Monitoring and Optimization

• Develop monitoring solutions to ensure the health and reliability of data pipelines and systems.
• Continuously optimize performance, storage, and costs of data infrastructure.

Qualifications

• Education:

- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.

• Experience:

- Min 3yrs of experience in software engineering, data engineering or a related role.

- Proven experience with data modeling, ETL/ELT pipelines, and data architecture design.

- Proficiency in programming languages such as Python, Java, or Scala.

- Strong knowledge of SQL and relational databases (e.g., PostgreSQL, Sybase, SQL Server).

• Desirable Technical Skills:

- Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure).

- Familiarity with data integration tools (e.g., Apache Airflow, Talend, Informatica) and streaming technologies (e.g., Kafka, Flink).

- Experience with data warehouse technologies (e.g., Snowflake, Redshift, BigQuery).

• Soft Skills:

- Strong analytical and problem-solving abilities.

- Effective communication and collaboration skills to work with diverse teams.

- Attention to detail and a proactive approach to ensuring data integrity.

Preferred Qualifications

• Experience in conforming to data governance frameworks.
• Knowledge of data lake architectures and unstructured data processing.
• Familiarity with machine learning workflows and AI-driven data applications.
• Certifications in relevant technologies (e.g., AWS Certified Data Analytics, Google Professional Data Engineer).

ABOUT GOLDMAN SACHS

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.

We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

The Goldman Sachs Group, Inc., 2024. All rights reserved.

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.