Design and implement a scalable data warehouse or data lakehouse to support analytics, reporting, and business KPIs
Develop and maintain reliable batch and/or streaming data pipelines from internal databases and external systems
Collaborate with stakeholders to translate business requirements into efficient data models and schemas
Establish and maintain data modeling standards and best practices
Implement monitoring, data quality controls, and observability for all data workflows
Provide well-structured datasets to enable self-service analytics for BI and data teams
Document the data platform, including lineage, definitions, and contracts, to create a shared source of truth for metrics

6+ years of experience in data engineering
Strong programming skills in Python
Proven track record of designing and delivering early-stage data platforms from concept (v1) to production
Strong expertise with modern data tooling (e.g., Snowflake/BigQuery/Redshift, dbt, Airflow/Dagster/Prefect, Fivetran/Airbyte, etc.)
Solid understanding of data modeling, ETL/ELT, and pipeline optimization
Strong knowledge of data quality, testing, and monitoring best practices
Upper-Intermediate English or higher
Experience with AI/ML data pipelines (WILL BE A PLUS)
Familiarity with finance/accounting datasets (WILL BE A PLUS)
Knowledge of compliance frameworks such as SOX or GDPR (WILL BE A PLUS)
Experience mentoring junior engineers (WILL BE A PLUS)

Senior Data Engineer

Key skills