Software Engineering

Goldman Sachs Bank AG; Stockholms kommun; On-site; SEK 502,200 - 781,200; Full time

Benefits offered by this job

Healthcare & Medical Insurance

Competitive vacation policies

Financial wellness support

On-site fitness centers

Child care services

Job summary

A major global investment bank is seeking a Data Engineer to develop the AI and analytics capabilities on its modern data platform. The successful candidate will design and support data pipelines, ensuring data quality and performance. Key qualifications include expertise in Python or Java, SQL proficiency, and experience with data processing frameworks such as Apache Spark. This role demands problem-solving skills within a delivery-focused team, contributing to critical data assets and enhancing analytics capabilities.

Qualifications

• Strong hands-on programming experience in Python or Java.
• Good working knowledge of SQL, including troubleshooting and optimization.
• Experience working with distributed data processing frameworks like Apache Spark.

Responsibilities

• Design, build, test and support data pipelines on a modern data platform.
• Develop raw, refined and curated datasets for analytics and reporting.
• Implement controls to verify data completeness and accuracy.

Skills

Python

Java

SQL

Apache Spark

Education

Bachelor’s or master’s degree in a relevant discipline

Tools

Apache Kafka

Snowflake

Databricks

Hadoop

Job description

The Opportunity

Join a team building the data foundations that support the firm’s AI and analytics capabilities. This role sits within the engineering effort to develop a modern Lakehouse and AI data platform that enables reliable, well-governed and high-performing data use across the firm.

At Goldman Sachs, engineering teams are positioned at the centre of the business, building scalable systems, solving complex technical problems and turning data into action. In data engineering roles, the emphasis is on designing, building and maintaining large-scale data platforms, delivering production pipelines, improving reliability and quality, and partnering closely with users of the platform.

This is a delivery-focused role for engineers who want to build robust data assets in production, work with modern data technologies, and grow over time within the firm. You will contribute to the data models, pipelines and platform capabilities that underpin analytics, operational decision-making and emerging AI use cases.

Role Summary

As a Data Engineer, Lakehouse and AI Data Platform, you will design, build, test and support data pipelines and curated datasets on the firm’s modern data platform. You will work across ingestion, transformation, modelling, optimisation and data quality, helping to deliver data products that are reliable, scalable and fit for purpose.

The role is suited to engineers who are comfortable writing code, working with SQL and distributed data processing, and solving practical delivery problems in a team environment. More experienced candidates may also contribute to technical design, platform standards and the shaping of delivery approaches across a wider set of use cases.

Key Responsibilities

• Build, enhance and support batch and streaming data pipelines on the Lakehouse and AI data platform.
• Refactor or modernise existing data flows where needed to improve reliability, performance and maintainability.
• Ensure data pipelines are production-ready, well tested and operationally supportable.

Data Modelling and Curation

• Develop raw, refined and curated datasets that support analytics, reporting and AI use cases.
• Apply sound data modelling principles to represent business entities, relationships and historical change accurately.
• Work with consumers to shape data products that are usable, well documented and aligned to business needs.

Data Quality and Reconciliation

• Implement controls to validate completeness, accuracy and consistency of data across pipelines and datasets.
• Use reconciliation approaches to build confidence in production outputs and investigate breaks where they arise.
• Contribute to clear standards for testing, monitoring and issue resolution.

Delivery and Partnership

• Work closely with engineers, platform teams and data consumers to deliver agreed outcomes to time and quality expectations.
• Communicate clearly on progress, risks, dependencies and design choices.

Skills and Experience

Required

• Bachelor’s or master’s degree in a relevant discipline, or equivalent practical experience, with evidence of strong quantitative skills or data engineering expertise.
• Strong hands‑on programming experience in PythonorJava.
• Good working knowledge of SQL, including troubleshooting, optimisation and data analysis.
• Ability to learn new tools, internal platforms and delivery workflows quickly.
• Familiarity with software engineering fundamentals, including version control, testing, release discipline and CI/CD practices.

Data Engineering Capability

• Understanding of temporal data modelling, including the handling of historical state and change over time.
• Knowledge of schema design, schema evolution and data compatibility considerations.
• Understanding of partitioning, clustering and other techniques used to improve data performance at scale.
• Ability to make sensible design choices across normalised and denormalised models, and between natural and surrogate keys.
• Practical approach to data quality, reconciliation and root‑cause analysis.
• Experience building or supporting production data pipelines in a collaborative engineering environment.
• Experience working with distributed data processing frameworks such as Apache Spark.
• Working knowledge of common data formats such as JSON,AvroandParquet.

Technology Environment

The role will involve working with a modern and evolving data stack. Candidates are not expected to have deep expertise in every tool from day one but should bring relevant experience and the ability to work across comparable technologies.

Examples of technologies in scope include:

• Data processing and logic:ANSI SQL, Apache Spark, Kafka
• Platforms and storage:Snowflake, Apache Iceberg, Databricks, Hadoop ecosystem technologies, Sybase IQ
• Engineering and deployment:CI/CD tooling, containerised or Kubernetes-based deployment approaches where relevant

You will also work with internal data management and platform tooling, so a practical and adaptable engineering mindset is important.

What We Are Looking For

We are looking for engineers who can deliver well‑structured, reliable solutions in production and who take ownership of the quality of the work they build. The role suits candidates who are technically strong, pragmatic and comfortable working in a fast‑paced environment where data platforms support important business outcomes.

Stronger candidates will typically demonstrate:

• sound judgement in technical trade‑offs
• attention to detail in data correctness and testing
• a clear and structured approach to problem solving
• willingness to work closely with stakeholders and partner teams
• an interest in developing long‑term expertise within the firm

Benefits at Goldman Sachs

Healthcare & Medical Insurance

We offer a wide range of health and welfare programs that vary depending on office location. These generally include medical, dental, short‑term disability, long‑term disability, life, accidental death, labor accident and business travel accident insurance.

Vacation Policies

We offer competitive vacation policies based on employee level and office location. We promote time off from work to recharge by providing generous vacation entitlements and a minimum of three weeks expected vacation usage each year.

Financial Wellness & Retirement

We assist employees in saving and planning for retirement, offer financial support for higher education, and provide a number of benefits to help employees prepare for the unexpected. We offer live financial education and content on a variety of topics to address the spectrum of employees’ priorities.

Health Services

We offer a medical advocacy service for employees and family members facing critical health situations, and counseling and referral services through the Employee Assistance Program (EAP). We provide Global Medical, Security and Travel Assistance and a Workplace Ergonomics Program. We also offer state‑of‑the‑art on‑site health centers in certain offices.

Fitness

To encourage employees to live a healthy and active lifestyle, some of our offices feature on‑site fitness centers. For eligible employees we typically reimburse fees paid for a fitness club membership or activity (up to a pre‑approved amount).

Child Care & Family Care

We offer on‑site child care centers that provide full‑time and emergency back‑up care, as well as mother and baby rooms and homework rooms. In every office, we provide advice and counseling services, expectant parent resources and transitional programs for parents returning from parental leave. Adoption, surrogacy, egg donation and egg retrieval stipends are also available.

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.

We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process.