About the role
Must have:
- At least 4 years of experience as a Data Engineer working with GCP cloud-based infrastructure & systems.
- Deep knowledge of Google Cloud Platform and cloud computing services.
- Extensive experience in design, build, and deploy data pipelines in the cloud, to ingest data from various sources like databases, APIs or streaming platforms.
- Proficient in database management systems such as SQL (Big Query is a must), NoSQL. Candidate should be able to design, configure, and manage databases to ensure optimal performance and reliability.
- Programming skills (SQL, Python, other scripting).
- Proficient in data modeling techniques and database optimization. Knowledge of query optimization, indexing, and performance tuning is necessary for efficient data retrieval and processing.
- Knowledge of at least one orchestration and scheduling tool (Airflow is a must).
- Experience with data integration tools and techniques, such as ETL and ELT Candidate should be able to integrate data from multiple sources and transform it into a format that is suitable for analysis.
- Knowledge of modern data transformation tools (such as DBT, Dataform).
- Excellent communication skills to effectively collaborate with cross-functional teams, including data scientists, analysts, and business stakeholders. Ability to convey technical concepts to non-technical stakeholders in a clear and concise manner.
- Ability to actively participate/lead discussions with clients to identify and assess concrete and ambitious avenues for improvement.
- Tools knowledge: Git, Jira, Confluence, etc.
- Open to learn new technologies and solutions.
- Experience in multinational environment and distributed teams.
Good to have:
- Certifications in big data technologies or/and cloud platforms.
- Experience with BI solutions (e.g. Looker, Power BI, Tableau).
- Experience with ETL tools: e.g. Talend, Alteryx
- Experience with Apache Spark, especially in GCP environment.
- Experience with Databricks.
- Experience with Azure cloud-based infrastructure & systems.