About the role
structured by ORIWe are seeking a skilled and proactive Data Engineer to join our collaborative, fast-paced Agile team. In this role, you will design and build robust data pipelines, optimize complex datasets, and develop data quality models to ensure our data is accurate, accessible, and ready for analytical use.
What you will do
- Data Pipeline & Architecture: Build, maintain, and troubleshoot moderately complex data pipelines (using Airflow) to ingest, transform, and aggregate data from disparate sources.
- Data Quality & Modeling: Design and implement data models, optimize performance, and develop rules/tracking processes to support data quality models based on data characteristics.
- Analysis & Interpretation: Perform design, creation, and deep-dive interpretation of large, highly complex datasets.
- Agile Project Delivery: Organize workflows, manage time effectively, and complete tasks accurately within budget and on time in a rapid development environment.
- Collaboration & Communication: Work independently under minimal supervision while maintaining effective, clear communication with peers, project leads, and management.
What they are looking for
- 3+ years of hands-on experience in software or data engineering with strong proficiency in Python and SQL.
- 2+ years of experience working with enterprise relational databases and cloud warehouses (e.g., PostgreSQL, MySQL, BigQuery).
- Practical experience building and orchestrating ETL/ELT pipelines using workflow management tools like Apache Airflow.
- Hands-on experience developing within a Google Cloud Platform (GCP) environment (Cloud Storage, BigQuery).
- Demonstrated experience with version control (GitHub) and collaboration tools (Jira, Confluence).
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field.
Nice to have
- Hands-on experience managing directed acyclic graphs (DAGs) in Google Cloud Composer.
- Prior exposure to modern enterprise data platforms such as Snowflake or Databricks.
- Understanding of streaming data frameworks (e.g., Apache Pub/Sub, Kafka) and CI/CD deployment pipelines.
Full posting text
We are seeking a skilled and proactive Data Engineer to join our collaborative, fast-paced Agile team. In this role, you will design and build robust data pipelines, optimize complex datasets, and develop data quality models to ensure our data is accurate, accessible, and ready for analytical use. The ideal candidate has strong foundational experience in Google Cloud Platform (GCP), relational databases, and modern data orchestration tools.
What You’ll Do
Data Pipeline & Architecture: Build, maintain, and troubleshoot moderately complex data pipelines (using Airflow) to ingest, transform, and aggregate data from disparate sources.
Data Quality & Modeling: Design and implement data models, optimize performance, and develop rules/tracking processes to support data quality models based on data characteristics.
Analysis & Interpretation: Perform design, creation, and deep-dive interpretation of large, highly complex datasets.
Agile Project Delivery: Organize workflows, manage time effectively, and complete tasks accurately within budget and on time in a rapid development environment.
Collaboration & Communication: Work independently under minimal supervision while maintaining effective, clear communication with peers, project leads, and management.
What Experience You Need
3+ years of hands-on experience in software or data engineering with strong proficiency in Python and SQL.
2+ years of experience working with enterprise relational databases and cloud warehouses (e.g., PostgreSQL, MySQL, BigQuery).
Practical experience building and orchestrating ETL/ELT pipelines using workflow management tools like Apache Airflow.
Hands-on experience developing within a Google Cloud Platform (GCP) environment (Cloud Storage, BigQuery).
Demonstrated experience with version control (GitHub) and collaboration tools (Jira, Confluence).
Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field.
What Could Set You Apart
Hands-on experience managing directed acyclic graphs (DAGs) in Google Cloud Composer.
Prior exposure to modern enterprise data platforms such as Snowflake or Databricks.
Understanding of streaming data frameworks (e.g., Apache Pub/Sub, Kafka) and CI/CD deployment pipelines.
Seniority level: Mid-Senior level
Employment type: Full-time
Industries: Financial Services