What you will do
- Build, test, document, and deploy reliable data pipelines, working with diverse data systems such as Snowflake, ClickHouse, Postgresql, S3 (CSV, Parquet, spreadsheets) and APIs (internal and SaaS).
- Provide a robust dbt runtime environment for Analytics Engineers, offering guidance and support in building resilient transformations while ensuring data governance for our existing ~1300 models.
- Proactively contribute to the evolution of our Internal Data Platform by proposing new ideas and exploring innovative big data tools. Our Platform is a critical product used by multiple departments across the company.
- Build and maintain the infrastructure of our Internal Data Platform using DevOps practices, ensuring scalability, reliability, and security.
- Effectively communicate and collaborate with a broad audience, tailoring your message to individuals with varying levels of technical expertise.
- Data: Python, Snowflake, dbt, Dagster, Sling, Fivetran.
- DevOps: AWS, Terraform, k8s, Github Actions.
What you need to succeed
- Strong strategic thinking skills, demonstrating an understanding of analytics needs in the business domain and proposing appropriate technical solutions.
- Autonomy and excellent people and time management skills to efficiently prioritize tasks and collaborate effectively within a distributed team.
- Ability to think outside the box, exhibiting a knack for finding the most suitable tech solutions to complex problems.
- Effective communication skills to engage with a diverse audience, including both technical and non-technical stakeholders.
- Knowledge of multi-threading, concurrency, and MPP technologies.
- Professional English (our team is international).
- 5+ years experience in Data Engineering
- Proficiency in Python and SQL
- Deep knowledge of data warehouses (Snowflake, BigQuery, Clickhouse …)
- Deep understanding of Data Architecture patterns
- Production experience with Data Orchestration solutions (Airflow, dbt…)
- Cloud computing
Bonus points
- Experience working with and deploying LLM models.
- Prior experience in building and launching a real product, either professionally or personally.
- Previous work experience in a scale-up environment, handling rapid growth and evolving challenges.
- Production experience with any of: AWS, k8s, Snowflake, Dagster
0 applies
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