Key Responsibilities:
- Partner with clients to understand their data landscape, challenges, and business goals
- Design and implement scalable data pipelines, architectures, and integration workflows
- Build ETL/ELT processes to ingest data from diverse sources
- Develop data models and warehouse architectures that support analytics and BI
- Conduct technical discovery sessions and translate business needs into technical solutions
- Communicate progress and recommendations to both technical and business stakeholders
- Document solutions and enable client teams to own what you have built
- Contribute insights from client work to inform our internal product development
Core Technical Requirements Essential Skills
SQL Expertise:
- Advanced query optimisation and performance tuning
- Complex data transformation and aggregation
- Experience with large-scale data processing
Python Programming:
- Data processing and manipulation libraries
- Script automation and pipeline development
- ETL/ELT process implementation
Cloud Platform Experience
- Experience with at least one major cloud platform (AWS, GCP, or Azure)
- Data warehouse or data Lakehouse experience (Snowflake, BigQuery, Redshift, Databricks)
Data Pipeline & Transformation
- Hands-on experience with orchestration tools (Airflow, Prefect, Dagster)
- Familiarity with transformation frameworks (dbt, SQLMesh, Spark)
- Comfortable deploying and working with open-source tools
