Senior HR Data Partner

SBM Offshore; Porto; On-site; EUR 55,000 - 85,000; Full time

Job summary

SBM Offshore seeks a Senior HR Data Partner Data Engineer to design, build and maintain HR data infrastructure and analytics solutions. You will create reliable data pipelines and enable data-driven decision making across the organization.

Collaborate with HR analytics teams to prepare data for analysis, engineer features for models, and optimize storage and query performance in data warehouses and data lakes using Python and SQL.

Qualifications

• 3+ years experience in ETL systems and big data tools.
• Experience with data modeling (star/snowflake schemas) and data warehousing.
• Proficient in Python and SQL; strong data visualization tooling knowledge.

Responsibilities

• Build and Maintain Data Infrastructure
• Data Pipeline Development: Design, implement, and manage data pipelines that extract, transform, and load data from various sources to data warehouses or data lakes.
• Data Integration: Combine data from diverse sources to create a unified data source.
• Optimize Data Storage and Query Performance
• Performance Tuning: Optimize queries, data structures, and indexing strategies for large datasets.
• Troubleshooting and Debugging: Resolve issues within data pipelines and improve reliability.
• Support Data Analysis and Machine Learning Initiatives
• Data Preparation for Analysis: Structure and prepare data for analysts and ML models.
• Feature Engineering: collaborate with HR Reporting and Analytics teams to create data features for models.
• Automate Data Processing and Workflow Management
• Workflow Orchestration: automate data workflows for consistency.
• Data Analysis: Use SQL, Python, and BI tools to identify trends and correlations.

Skills

Data Pipelines

ETL

SQL

Python

Big Data

BI Tools

Education

Degree in Computer Science / IT / Software Engineering / Statistics / Data Science

Tools

AWS

Google Cloud Platform

Azure

Job description

Select how often (in days) to receive an alert: Imagine your career taking you to the depths of innovation and the heights of impact. Our people enable continuous progress. Their commitment, collective expertise, and unique capabilities are the engine room behind SBM Offshore's True. Blue. Transition. - shaping the future of energy, and beyond.

About Us

SBM Offshore is a global leader in deepwater ocean infrastructure, delivering floating production solutions across the full asset lifecycle-from design and construction to installation and operation. Supported by a global team of more than 8,000 professionals, the Company operates a long-term, asset-backed business model that delivers high-availability assets and predictable cash flows. SBM Offshore combines engineering expertise, operational reliability, and selective innovation to support safe, efficient, and lower-carbon energy production, while extending its capabilities into new opportunities across the blue economy.

Purpose

• The Senior HR Data Partner Data Engineer designs, builds, and maintains the infrastructure that enables the collection, storage, and processing of data within the HR function. Is responsible for designing, developing, and implementing comprehensive analytics solutions that facilitate data-driven decision-making across an organization.

Responsibilities

• Build and Maintain Data Infrastructure
• Data Pipeline Development: Design, implement, and manage data pipelines that extract, transform, and load data from various sources to data warehouses or data lakes.
• Data Integration: Combine data from diverse sources (databases, APIs, file systems, and streaming services) to create a unified, organized data source.
• Optimize Data Storage and Query Performance
• Performance Tuning: Optimize queries, data structures, and indexing strategies to ensure efficient and fast data retrieval, especially for large datasets.
• Troubleshooting and Debugging: Resolve issues within data pipelines, monitor for performance bottlenecks, and implement solutions to improve reliability and efficiency.
• Support Data Analysis and Machine Learning Initiatives
• Data Preparation for Analysis: Structure and prepare data to be easily accessed and queried by data scientists, analysts, and machine learning models.
• Feature Engineering: In collaboration with the HR Reporting and Analytics team (and other data teams), create and process data features used in predictive models, ensuring data pipelines meet analytical requirements.
• Automate Data Processing and Workflow Management
• Workflow Orchestration: to automate and schedule data workflows, ensuring that data pipelines run consistently and with minimal manual intervention.
• Data Analysis:
• Use statistical techniques and tools (such as SQL, Python, R, or Excel) to analyze complex datasets and identify trends, patterns, and correlations.
• Conduct exploratory data analysis (EDA) to understand data distributions and relationships.

Education

• Majors: A degree in Computer Science, Information Technology, Software Engineering, Statistics or Data Science

Experience

• +3 years experience working ETL systems, and big data tools.
• Performance Tuning: Skills in tuning queries and optimizing the data pipeline for faster, more efficient data flow.
• Data Modeling: Experience designing efficient data models (star schema, snowflake schema) for relational and dimensional databases to improve data retrieval and analysis.
• Data Warehousing: Hands-on experience with data warehousing solutions like Amazon Redshift, Google BigQuery, Snowflake, or Azure Synapse (Azure Synapse preferred) for storing, processing, and querying large datasets.
• Cloud Platforms: Practical experience with cloud platforms such as AWS, Google Cloud Platform, or Microsoft Azure (Microsoft Azure preferred).
• Data Lakes: Working with data lakes (e.g., AWS S3, Azure Data Lake), particularly when handling unstructured or semi-structured data at scale.
• Data Architecture: Working knowledge of building data architectures that scale, including data lakes, data marts, and data warehouses.
• Python and SQL: Proficiency in Python for data manipulation and scripting, as well as SQL for data querying and management.
• Business Intelligence: Practical experience in data visualization tools (Tableau, Looker, Power BI)

Tools and data governance

• Compliance
• Analytics and reporting
• Business Partnering
• Digital savvy
• HR Acumen
• Systems and Technology
• Technical Data Management

General Information

SBM Offshore N.V. is a listed holding company that is headquartered in Amsterdam. It holds direct and indirect interests in other companies that collectively with SBM Offshore N.V. form the SBM Offshore Group (the Company). For further information, please visit our website at www.sbmoffshore.com. The companies in which SBM Offshore N.V., directly and indirectly, owns investments are separate entities.

SBM Offshore is proud to be an Equal Employment Opportunity and Assertive Action employer.SBM Offshore does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by appropriate law. All employment is decided on the basis of qualifications, merit, and business need.