Hybrid Cloud Data Engineer — Snowflake & Databricks

OSRAM Opto Semiconductors (Malaysia) Sdn Bhd

Carnaxide

Híbrido

EUR 55 000 - 75 000

Tempo integral

Há 13 dias

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Resumo da oferta

ams OSRAM is seeking a senior data analytics professional to partner with data scientists, analysts and stakeholders to translate data needs into scalable cloud solutions. You will help design data models, implement pipelines, and ensure data integrity while adhering to best practices.

The role requires hands-on SQL/Python, BI reporting with Power BI, and experience with Snowflake/Databricks, NiFi, and Azure Data Factory.

Qualificações

Bachelor’s degree in Computer Science, Software Engineering or similar.
Minimum 5 years of related working experience with cloud data warehouse technologies, preferably Snowflake and/or Databricks.
Hands-on experience in data warehouse modelling preferably with data vault 2.0 and/or star schema.
In-depth understanding of relational databases (SQL) and ETL (Extract, transform, load) frameworks.
Experienced in data staging with SQL and Python, data visualization with PowerBI, data integration using Apache NiFi, Theobald Universal Xtract, and Azure Data Factory, as well as orchestrating data pipelines with dbt and Apache Airflow.
Problem-solving attitude and excellent communication skills.
Excellent organizational skills with the ability to communicate project goals and objectives, project status and deliverables.
Fluent in English for communicating with global teams and stakeholders.

Responsabilidades

Work closely with data scientists, business analysts and other stakeholders to understand their data requirements and translate them into technical specifications and data models.
Collaborate with data architects to design and implement cloud-based data solutions that align with business needs.
Facilitate internal knowledge sharing to ensure team members are informed about the latest best practices.
Implement scalable and robust data pipelines from various source systems.
Apply business rules and transformations using SQL or Python.
Secure data models applying object and row level security.
Develop and document best practices and ensure they are effectively implemented across the team.
Analyze and address issues related to data integrity, data design and both functional and technical aspects of the Cloud Data Warehouse.
Communicate effectively about issues, solutions, and best practices with relevant stakeholders.
Perform cost and performance-based optimization of data transfer processes.
Continuously monitor and improve the efficiency and performance of data pipelines.