Senior Data Engineer (Bigquery, Dbt, Python, Data Modeling)
Summary
Build and maintain scalable data pipelines and warehouses using BigQuery, dbt, Python, and GCP services to ensure reliable, high-quality data for analytics and reporting.
- Design, develop, operationalize robust and scalable data pipelines with automated data quality checks to support business needs and demonstrate ownership of live data pipelines.
- Proficiency understanding and implementing data life cycles, data lineage, custom metadata, and data governance.
- Proficiency implementing BigQuery SQL procedures, functions, and similar, with actionable logging
- Optimize ETL processes and data workflows to ensure abiding by performance constraints, for efficiency and scalability.
- Comfortably lead designing and building of development to production data pipelines from data ingestion to consumption using GCP services, Python, BigQuery, DBT, SQL, Apache Airflow, Celigo.
- Expertise in JSON, XML, text parsing using Dataflow, Python, or batch jobs.
- Advocates and practices software best practices in leveraging reusable components in implementation.
- Design, develop and maintain robust, and scalable data models and schemas to support analytics and reporting requirements.
- Optimize data processing performance, ensure high availability, scalability of data systems and solutions.
- Implement monitoring and alerting mechanisms to proactively identify and resolve issues.
- Ensure data quality and consistency through rigorous testing and validation processes in development and production tiers.
- Troubleshoot and resolve data-related issues promptly.
- Create, update, and maintain technical documentation of the data processes, pipelines, and models.
- Stay updated with industry trends and technologies to continuously improve our data engineering practices.
- 6+ years of experience in Data / ETL Engineering, as well as Data / ETL Architecture and pipeline development with a minimum of 2+ years of working experience as Google Cloud Platform (GCP) developer.
- Bachelor-level degree in Computer Science, MIS, or CIS, or equivalent experience.
- Proven experience in building and maintaining a scalable Data Warehouse in a cloud-based data platform, preferably in Google’s BigQuery.
- Experience with the primary managed data services within GCP, including DataProc, Dataflow, BigQuery etc.
- Proficiency in SQL, DBT, Python (Apache Airflow, Composer) and hands-on experience with ETL tools like Talend, Fivetran or similar.
- Proficiency in Git for version control
- Experience with DBT for data transformation.
- Proven experience in high-quality designing, building and maintaining ETL processes, automated data quality checks and reusable ETL components.
- Familiarity with Data Lake and Data Warehousing concepts and Data Modelling techniques.
- Familiarity with concepts like star schema, snowflake schema, standardization, normalization, fact and dimension tables.
- Strong problem-solving skills and the ability to work independently as well as collaboratively.
- Excellent communication skills and the ability to articulate technical concepts to non-technical stakeholders.
- Bachelor-level degree in Computer Science, MIS, or CIS, or equivalent experience.
- Salary paid in USD to Payoneer or Argentinian/USA bank.
- We cover 16 national holidays and 10 days of vacation.
- Ability to work with some of the best Data engineers in the World.